Jobs

We are:

A forward-thinking services company at the forefront of AI-native innovation. We partner with enterprise clients to create next-generation, agent-powered workflows engineered to scale in real-world settings. Our engineers embed deeply with customers, moving projects beyond experimentation into operational reality.

You are:

An AI Native Engineer with a minimum of 5 years of experience building cloud-native solutions, and deep expertise in designing and deploying agentic systems, especially for enterprise environments. You are a critical thinker that thrives in ambiguity, delivering concrete results by designing, building, and running custom AI agents that augment workflows and scale across modern infrastructure. You’ll help shape the playbook for how enterprises adopt and scale AI-native engineering globally.

The Work:

You’ll embed directly with clients — acting as both technologist and trusted advisor. You’ll partner with stakeholders to define use cases, rapidly prototype, and deploy agentic workflows that are robust, secure, and operational in complex enterprise domains. Often, these will be completely net new platforms and systems that need to be stitched together in our clients' environments alongside our Ecosystem partners.

Responsibilities:

Agent Architecture and Engineering: Design and engineer enterprise-ready AI agents encompassing retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.

AI Platform Integration: Develop abstraction layers across AI providers (Anthropic, Google, OpenAI, etc. ) to enable seamless integration and enablement.

Cloud-Native Engineering: Leverage containerization (Kubernetes, Docker), microservices, serverless, event-driven architectures, CI/CD, and observability to deliver scalable AI-native systems.

Domain-Specific Workflows: Tailor and deploy agentic applications across verticals — e.g., finance,

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Software Engineering Job Details About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. About the Role The Product Forward Deployed Engineering (FDE) team is Salesforce's zero-to-one engine for new agentic product innovation. We embed directly with our most strategic customers to validate emerging AI capabilities, harden the platform under real-world conditions, and transform every field insight into repeatable patterns that shape the product roadmap. We are looking for a Senior Director, Forward Deployed Engineering to lead our Agentforce Supply Chain organization. This is a senior technical leadership role at the intersection of AI, enterprise supply chain, and product development. You'll embed expert engineering talent with strategic customers to own and evolve the agentic workflow infrastructure powering Agentforce Supply Chain — purpose-built for complex, multi-party manufacturing environments. In doing so, you'll incubate emerging capabilities, validate pre-GA and early GA features, and generate the product signal that drives roadmap priorities — ensuring what we learn in the field directly shapes what gets built next. Your Impact Leadership & Team Management Lead a High-Performing Team: Recruit, mentor, and develop a global team of Produ

What you will do

In this role you will build the agentic systems that power Teradata's next generation of AI-driven analytics - intelligent agents that reason over enterprise data, invoke Vantage capabilities as tools, and complete multi-step analytical tasks autonomously.

You will design and implement agent skills and plugins that extend the Teradata agent harness, build evaluation frameworks to measure agent quality, and contribute to the reliability and performance of agent workflows running on Vantage. Your work directly enables customers to move from asking Teradata questions to delegating analytical tasks to AI agents.

Success looks like agents in production that solve real customer problems - with measurable accuracy, latency, and reliability benchmarks that outperform what is possible on Snowflake Cortex or Databricks Genie.

Who you will work with

You will join a focused team of AI engineers within Teradata's AI Apps, Analytics, and UX Engineering organization, working on the most technically ambitious part of the Teradata product roadmap. We ship code, not demos.

This role reports to the Senior Manager of AI Engineering and collaborates closely with Staff AI Engineers, the Agent Platform team, and Product Management. You will have access to Teradata's world-class data infrastructure and the opportunity to shape how enterprise agents work at scale.

What makes you a qualified candidate
3-6 years of software engineering experience with at least 2 years building agentic AI systems in production - not just RAG pipelines or chatbots. Hands-on experience implementing agent skills, plugins, or tools that extend an agent harness (Claude Code, OpenCode, Codex, OpenClaw, LangGraph, or equivalent). Proficiency in Python; Go experience is a strong advantage. Understanding of agent planning loops, tool-calling protocols, function calling APIs (OpenAI, Anthropic, or Google format), and prompt engineering for reliability.
What you will bring
Op

We are:

A forward-thinking services company at the forefront of AI-native innovation. We partner with enterprise clients to create next-generation, agent-powered workflows engineered to scale in real-world settings. Our engineers embed deeply with customers, moving projects beyond experimentation into operational reality.

You are:

An AI Native Engineer with a minimum of 5 years of experience building cloud-native solutions, and deep expertise in designing and deploying agentic systems, especially for enterprise environments. You are a critical thinker that thrives in ambiguity, delivering concrete results by designing, building, and running custom AI agents that augment workflows and scale across modern infrastructure. You’ll help shape the playbook for how enterprises adopt and scale AI-native engineering globally.

The Work:

You’ll embed directly with clients — acting as both technologist and trusted advisor. You’ll partner with stakeholders to define use cases, rapidly prototype, and deploy agentic workflows that are robust, secure, and operational in complex enterprise domains. Often, these will be completely net new platforms and systems that need to be stitched together in our clients' environments alongside our Ecosystem partners.

Responsibilities:

Agent Architecture and Engineering: Design and engineer enterprise-ready AI agents encompassing retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.

AI Platform Integration: Develop abstraction layers across AI providers (Anthropic, Google, OpenAI, etc. ) to enable seamless integration and enablement.

Cloud-Native Engineering: Leverage containerization (Kubernetes, Docker), microservices, serverless, event-driven architectures, CI/CD, and observability to deliver scalable AI-native systems.

Domain-Specific Workflows: Tailor and deploy agentic applications across verticals — e.g., finance,

Our Company

At Teradata, we believe that people thrive when empowered with trusted information. Our technology disrupts current thinking and delivers innovative and trusted solutions for the world's toughest data and analytics challenges—all powered by people like you.

What You Will Do

In this role you will build the agentic systems that power Teradata's next generation of AI-driven analytics — intelligent agents that reason over enterprise data, invoke Vantage capabilities as tools, and complete multi-step analytical tasks autonomously.

You will design and implement agent skills and plugins that extend the Teradata agent harness, build evaluation frameworks to measure agent quality, and contribute to the reliability and performance of agent workflows running on Vantage. Your work directly enables customers to move from asking Teradata questions to delegating analytical tasks to AI agents.

Success looks like agents in production that solve real customer problems — with measurable accuracy, latency, and reliability benchmarks that outperform what is possible on Snowflake Cortex or Databricks Genie.

Who You Will Work With

You will join a focused team of AI engineers within Teradata's AI Apps, Analytics, and UX Engineering organization, working on the most technically ambitious part of the Teradata product roadmap. We ship code, not demos.

This role reports to the Senior Manager of AI Engineering and collaborates closely with Staff AI Engineers, the Agent Platform team, and Product Management. You will have access to Teradata's world-class data infrastructure and the opportunity to shape how enterprise agents work at scale.

What Makes You a Qualified Candidate

3–6 years of software engineering experience with at least 2 years building agentic AI systems in production — not just RAG pipelines or chatbots. Hands-on experience implementing agent skills, plugins, or tools that extend an agent harness (Claude Code, OpenCode, Codex, OpenClaw, LangGraph,

We are:

A forward-thinking services company at the forefront of AI-native innovation. We partner with enterprise clients to create next-generation, agent-powered workflows engineered to scale in real-world settings. Our engineers embed deeply with customers, moving projects beyond experimentation into operational reality.

You are:

An AI Native Engineer with a minimum of 5 years of experience building cloud-native solutions, and deep expertise in designing and deploying agentic systems, especially for enterprise environments. You are a critical thinker that thrives in ambiguity, delivering concrete results by designing, building, and running custom AI agents that augment workflows and scale across modern infrastructure. You’ll help shape the playbook for how enterprises adopt and scale AI-native engineering globally.

The Work:

You’ll embed directly with clients — acting as both technologist and trusted advisor. You’ll partner with stakeholders to define use cases, rapidly prototype, and deploy agentic workflows that are robust, secure, and operational in complex enterprise domains. Often, these will be completely net new platforms and systems that need to be stitched together in our clients' environments alongside our Ecosystem partners.

Responsibilities:

Agent Architecture and Engineering: Design and engineer enterprise-ready AI agents encompassing retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.

AI Platform Integration: Develop abstraction layers across AI providers (Anthropic, Google, OpenAI, etc. ) to enable seamless integration and enablement.

Cloud-Native Engineering: Leverage containerization (Kubernetes, Docker), microservices, serverless, event-driven architectures, CI/CD, and observability to deliver scalable AI-native systems.

Domain-Specific Workflows: Tailor and deploy agentic applications across verticals — e.g., finance,

We are seeking a Forward Deployed AI Engineer (FDE) to accelerate the real-world adoption of AI within our End-to-End System Test Automation. This role focuses on taking AI tools and prototypes and making them work reliably inside complex engineering environments. You will embed closely with system test engineers, automation framework/ test owners and development teams to adapt, harden and operationalize AI-driven workflows. This is a hands-on engineering role for individuals who thrive in ambiguity, enjoy working close to real users and can turn AI potential into measurable productivity gains.

Key Responsibilities:Forward Deployment of AI into Test Automation and turn AI prototypes into production-ready, repeatable solutions

Embed with system test and automation teams to:
Understand real testing workflows, constraints, and failure modes
Identify where AI can safely and effectively reduce manual effort
Adapt AI workflows to work with:
Existing automation frameworks
Real test data, schemas, and configurations

Agentic AI Implementation & TuningImplement and customize agentic AI workflows that:
Interpret requirements, schemas, or models
Assist in generating structured test assets
Tune AI behavior based on:
Real test outcomes
Failure analysis and feedback
Debug and resolve AI issues in live engineering environments

AI Tooling & Platform FeedbackWork with AI platforms (e.g., Qodo or similar) to:
Extend functionality where needed
Configure prompts, workflows, and validation layers
Evaluate emerging AI tools and frameworks in real system test contexts
Feed practical insights back to platform and leadership teams:
What works
What fails
What should scale

Enablement, Documentation & GuardrailsDocument AI usage patterns and best practices
Help define guardrails for:
Safety-critical configurations
Invalid or destructive AI-generated outputs
Enable test engineers to adopt AI confidently and responsibly

Required Qualifications2+ years of hands-on experience in software engi

Founded in 2012, H2O.ai is on a mission to democratize AI. As the world’s leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built GenAI applications on their private data. With a focus on Sovereign AI—secure, compliant, and infrastructure-flexible deployments—H2O.ai delivers solutions that align with the highest standards of data privacy and control.

Our open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Chipotle, Workday, Progressive Insurance, and NIH.

H2O.ai partners include NVIDIA, Dell Technologies, Deloitte, Ernst & Young (EY), Snowflake, AWS, Google Cloud Platform (GCP), VAST Data and MinIO. H2O.ai’s AI for Good program supports nonprofit groups, foundations, and communities in advancing education, healthcare, and environmental conservation. With a vibrant community of 2 million data scientists worldwide, H2O.ai aims to co-create valuable AI applications for all users.

H2O.ai has raised 256 million from investors, including Commonwealth Bank, NVIDIA, Goldman Sachs, Wells Fargo, Capital One, Nexus Ventures and New York Life.

For more information, visit www.h2o.ai.

The Opportunity

We are looking for a Senior AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one.

You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes.

What You

Hi Professionals,

Title: Healthcare Senior NLP / LLM Engineer (MLOps & AWS)-Onsite Role,Need Local to TXExperience: 7+ Years
Location: Houston, TX (3 days/week onsite)

Mandatory Skills:

Strong expertise in NLP, Machine Learning, and Deep LearningProficiency in Python for ML/NLP solution developmentHands-on experience with LLMs, prompt engineering, and agentic workflows (e.g., LangGraph)Solid knowledge of data preprocessing, feature engineering, and data validationStrong MLOps skills: model versioning, CI/CD, pipelines, monitoring, retrainingExperience with Docker and KubernetesProficiency in SQL for data analysis and transformationExperience with AWS (EMR, Spark, PySpark, Bedrock)Knowledge of PostgreSQL or MySQLStrong understanding of testing, error analysis, and model validation "Disclaimer: E-Solutions Inc. provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state and local laws. We especially invite women, minorities, veterans, and individuals with disabilities to apply. EEO/AA/M/F/Vet/Disability.”

Healthcare Senior NLP / LLM Engineer (MLOps & AWS)-Onsite Role,Need Local to TX1AWS,NLP,health OR Healthcare,MLOps,LLMN/AC2CUnited States

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired bya collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizationsunlock the value of technology and build a more sustainable, more inclusive world.

Location This is an onsite role to be based in either Chicago, IL or Seattle, WA or Grand Rapids, MI or Scottsdale, AZ or Atlanta, GA.

About the job you're considering We are seeking a passionate and innovative Software Development Engineer in Test (SDET) to join our Quality Engineering team and lead the development of LLM- and agentic-based testing solutions. This role blends traditional automation expertise with cutting-edge AI technologies to build intelligent, scalable, and autonomous testing frameworks that redefine how we validate software quality.

Your role Design and implement end-to-end testing frameworks leveraging Large Language Models (LLMs) and agentic workflows. Develop and maintain automated test suites for UI, API, and data layers across multiple platforms. Collaborate with AI/ML engineers to integrate Natural Language Processing (NLP) models into testing pipelines. Build and manage test data pipelines for diverse applications and environments. Create and maintain CI/CD pipelines to support continuous testing and deployment. Identify and resolve environmental and data dependencies for comprehensive E2E testing. Lead defect triage, backlog grooming, and root cause analysis sessions. Your skills and experience Around 1 year of experience working in or supporting AIbased testing environments, or strong interest with handson exposure through projects or coursework. Working knowledge of at least one programming or scripting langua

Job Number: R0233768

Agentic AI Engineer

The Opportunity:

We are looking for a highly skilled Agentic AI Engineer to join our team, specializing in building autonomous, goal-oriented AI systems. You will play a crucial role in shifting our AI strategy from passive LLM chatbots to proactive, multi-agent orchestrations. In this role, you will utilize deep experience in agent orchestration frameworks, RAG, knowledge graphs, and fine-tuning Small Language Models (SLMs) for edge deployment.

What You'll Work On:

Design and implement intelligent agent architectures that can reason, plan, and take actions using LangChain, LangGraph, and AutoGen.Develop and deploy multi-agent systems using MCP (Model Context Protocol) and A2A (Agent-to-Agent) protocols to facilitate communication, tool usage, and collaborative task solving.Build advanced RAG pipelines integrating unstructured data with Knowledge Graphs (KG) to enhance reasoning accuracy and context retention.Fine-tune Small Language Models (SLMs) for specific domains and optimize them for edge device performance, including ONNX, GGML, or Ollama.Develop evaluation frameworks to test agent reliability, safety, and performance, moving from prototype to production, including ReAct loops and human-in-the-loop.

Join us. The world can’t wait.

You Have:

5+ years of experience in software development2+ years of experience with GenAI, LLMs, and agentic workflowsExperience with LangChain, LangGraph, AutoGen, or LlamaIndexExperience with Model Context Protocol (MCP) for tool integration and A2A for agent-to-agent collaborationExperience in RAG architecture and Knowledge Graphs, including Neo4j or NebulaGraphExperience fine-tuning LLMs or SLMs using Hugging Face, PEFT, or LoRAKnowledge of modern software design patterns, including microservice design or edge computingAbility to obtain a Secret clearanceBachelor’s degree in a Computer Science or AI field

Nice If You Have:

Experience deploying agentic systems in a production en

Agentic AI Engineer

The Opportunity:
We are looking for a highly skilledAgentic AI Engineerto join our team, specializing in building autonomous, goal-oriented AI systems. You will play a crucial role in shifting our AI strategy from passive LLM chatbots to proactive, multi-agent orchestrations. In this role, you will utilize deep experience in agent orchestration frameworks, RAG, knowledge graphs, and fine-tuning Small Language Models (SLMs) for edge deployment.

What You'll Work On:

Design and implement intelligent agent architectures that can reason, plan, and take actions using LangChain, LangGraph, and AutoGen.

Develop and deploy multi-agent systems using MCP (Model Context Protocol) and A2A (Agent-to-Agent) protocols to facilitate communication, tool usage, and collaborative task solving.

Build advanced RAG pipelines integrating unstructured data with Knowledge Graphs (KG) to enhance reasoning accuracy and context retention.

Fine-tune Small Language Models (SLMs) for specific domains and optimize them for edge device performance, including ONNX, GGML, or Ollama.

Develop evaluation frameworks to test agent reliability, safety, and performance, moving from prototype to production, including ReAct loops and human-in-the-loop.

Join us. The world can't wait.

You Have:

5+ years of experience in software development

2+ years of experience with GenAI, LLMs, and agentic workflows

Experience withLangChain, LangGraph,AutoGen, orLlamaIndex

Experience withModel Context Protocol (MCP)for tool integration andA2Afor agent-to-agent collaboration

Experience inRAGarchitecture andKnowledge Graphs, including Neo4j or NebulaGraph

Experience fine-tuning LLMs or SLMs using Hugging Face, PEFT, or LoRA

Knowledge of modern software design patterns, including microservice design or edge computing

Ability to obtain a Secret clearance

Bachelor's degree in a Computer Science or AI field

Nice If You Have:

Experience deploying agentic systems in a production environme

We are hiring as many as two Senior AI Engineers who can architect and ship agentic systems, swiftly. You will be embedded in the full product lifecycle: ideation, prototyping, testing, and iteration across multiple concurrent concepts. Our first platform targets compliance automation in regulated industries, starting with affordable housing, designed to scale horizontally. When something proves out, you go deep. When it doesn't, you let it go without sentiment and move to the next. If the products you launch draw early signs of product-market fit, the resources will be assigned accordingly to seize upon the opportunity and iterate.

What You'll Do

Design and deploy multi-agent orchestration systems using frameworks like LangGraph, CrewAI, AutoGen, or equivalent, and know when to roll your own
Build full-stack prototypes fast enough to validate or kill an idea within weeks, not quarters
Own the technical architecture on 2-4 parallel concepts at any point in time
Integrate LLMs, RAG pipelines, structured data sources, and external APIs into coherent product experiences
Oversee commercialization and enterprise-upgrading to bring MVPs to full launch
Instrument everything so decisions are data-driven, not vibes-driven
Collaborate directly with the principals. There is no middle layer here

Who You Are

You have built real agentic systems, not just demo apps. You understand tool use, memory architectures, multi-agent orchestration, and evaluation at a production level. You know the difference between a clever prototype and something that actually holds up under load
You move fast and you ship. You have launched products at startups where speed was the strategy, not just a nice-to-have. Weeks, not quarters
You are full-stack by necessity, not by title. Frontend, backend, infra, pipelines. You do what needs doing and figure out the rest on the fly
You have strong opinions about what makes software work and zero patience for unnecessary complexity. You woul

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired bya collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizationsunlock the value of technology and build a more sustainable, more inclusive world.
Location

This is an onsite role to be based in either Chicago, IL or Seattle, WA or Grand Rapids, MI or Scottsdale, AZ or Atlanta, GA.

About the job you're considering

We are seeking a passionate and innovative Software Development Engineer in Test (SDET) to join our Quality Engineering team and lead the development of LLM- and agentic-based testing solutions. This role blends traditional automation expertise with cutting-edge AI technologies to build intelligent, scalable, and autonomous testing frameworks that redefine how we validate software quality.

Your role
• Design and implement end-to-end testing frameworks leveraging Large Language Models (LLMs) and agentic workflows.
• Develop and maintain automated test suites for UI, API, and data layers across multiple platforms.
• Collaborate with AI/ML engineers to integrate Natural Language Processing (NLP) models into testing pipelines.
• Build and manage test data pipelines for diverse applications and environments.
• Create and maintain CI/CD pipelines to support continuous testing and deployment.
• Identify and resolve environmental and data dependencies for comprehensive E2E testing.
• Lead defect triage, backlog grooming, and root cause analysis sessions.

Your skills and experience
• Around 1 year of experience working in or supporting AIbased testing environments, or strong interest with handson exposure through projects or coursework.
• Working knowledge of at least one programming or scripting language such as Python (preferred), Java, or JavaScript.
• Basic to intermediate experience with test automation t

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Ledgent Technology, is seeking the following. Apply via Dice today!

No Corp-to-corp / No Third-Party Agencies**We're Hiring on behalf of our client for Lead Agentic AI Engineer**
Hybrid Onsite near Fullerton, CA
190,000 to 210,000 annual salary (DOE)

*:**
Full-Time, Direct Hire
*Lead AI Developer - Microsoft/.NET Platform (On Prem)**
.
Partnered with a client who is seeking Lead AI Developer to help shape the next generation of intelligent, production-grade AI inside a mission critical, on prem manufacturing platform.

They're looking for a senior AI engineer who can own architecture, hands on development, and technical leadership as they embed advanced

*agentic**
capabilities, secure tool ecosystems, and reliable LLM integrations across Microsoft-based stack.
*What You'll DoArchitect end to end AI capabilities within an on prem .NET environment (ASP.NET, services, SQL Server).Build a robust agent runtime that handles tool execution, task state, routing, retries, and safe boundaries.Integrate with hosted LLM providers using modern tool/function-calling patterns and quality guardrails.Develop and maintain secure MCP-style tool servers for SQL, internal APIs, and file/report systems.Implement human in the loop controls, auditability, secrets management, and least privilege access patterns.Drive observability across logs, metrics, tracing, and dashboards.Establish testing strategies spanning unit, integration, failure simulation, and contract testing.Provide architectural direction, mentorship, reviews, documentation, and golden-path patterns for future AI dev work.Support deployments, troubleshooting, and alignment of AI capabilities with product priorities.What You Bring7+ years building distributed, production systems (Ideally, in .NET/C# services).2 years with agentic AI architecture/integration experience in business environment (not personal projects).Stron

Lead AI Engineer (Gen AI Platform, Agentic AI & LLM Infrastructure & Orchestration)

{"description": "Lead AI Engineer (Gen AI Platform, Agentic AI & LLM Infrastructure & Orchestration)

Overview

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates wor

Our company

At Teradata, we believe that people thrive when empowered with better information. That’s why we built the most complete cloud analytics and data platform for AI. By delivering harmonized data, trusted AI, and faster innovation, we uplift and empower our customers—and our customers’ customers—to make better, more confident decisions. The world’s top companies across every major industry trust Teradata to improve business performance, enrich customer experiences, and fully integrate data across the enterprise.

What you will do

In this role you will:
• Lead the design and development of AI-native agentic workflows that enhance engineering productivity, observability intelligence, and end-to-end operational excellence across Teradata’s AI Platform.
• This is a Senior Individual Contributor role focused on building and deploying intelligent agents—not just integrating automation tools, but architecting AI-driven systems that reason, analyze, and act across telemetry, applications, and workflows.
• Architect and build AI agents for observability, automated root cause analysis, anomaly detection, and engineering productivity optimization.
• Design agentic workflows that integrate across telemetry pipelines, application stacks, and cloud infrastructure.
• Develop AI-driven tooling to accelerate development velocity, reduce operational toil, and improve MTTR.
• Apply LLMs, reasoning frameworks, and advanced AI patterns to automate complex debugging and system diagnostics.
• Drive AI-native development practices across apps, tooling, and platform engineering.
• Partner across engineering teams to embed intelligent automation into CI/CD, DevOps, and support workflows.
• Apply foundational AI skills to explore and implement ways AI can enhance productivity, innovation, and impact across our workforce.
• Your work will directly shape how Teradata builds, monitors, and operates its AI-powered platform. Success in this role means measurable improvements in engineer

Lead AI Engineer (Gen AI Platform, Agentic AI & LLM Infrastructure & Orchestration)

Overview

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.

Design, develop, test, deploy, and support A

Location: Remote (Global)

Compensation: Competitive, dependent on experience

Type: Full-Time Contractor (2+ months, potential to extend)

Reports to: Managing Partner

About HELO Solutions

HELO Solutions is an AI consulting and product development company. We build production AI systems — agents, automation platforms, and intelligent workflows — for enterprise clients across industries including CPG, financial services, legal, and music. We also develop our own AI products. We are a small, high-output team that ships fast, operates with minimal bureaucracy, and holds a high bar for work that actually runs in production and gets used.

About the Role

We are hiring an AI Engineer who has built agents that are live in production at real companies — not demos, not prototypes that died after a pitch, not research projects. We need someone who has shipped agentic systems that enterprises depend on every day, and who understands the full lifecycle: scoping the business problem, designing the agent architecture, integrating with messy enterprise systems, building evaluation and monitoring, and keeping it running reliably.

This role sits across two priorities equally: building our internal multi-agent AI platform and delivering agent-based solutions directly to enterprise clients. You will work closely with our engineering team and the Managing Partner. You will have significant autonomy and direct impact on both the product and the business.

Responsibilities

Design, build, and deploy AI agents and multi-agent systems that solve real business problems for enterprise clients.
Architect and implement agent orchestration — coordination, handoffs, shared state, and communication between specialized agents within our multi-agent platform.
Integrate agents with enterprise systems (ERPs, CRMs, accounting platforms, APIs) to execute workflows end-to-end in production environments.
Build evaluation frameworks and production monitoring for deployed agents — loggi

Agentic AI Engineer
Enterprise Integrations, Intelligent Automation & AI Platform Delivery

Department: IT & Digital Transformation
Reports to: Sr. Director, Infrastructure & BI
Type: 6 month contract

Location: Remote - US

The Opportunity
Accuris Technologies is executing a company-wide AI transformation across 40+ initiatives spanning Finance, Sales, Marketing, Legal, RevOps, Product, HR, and Customer Experience. We have a funded roadmap, active enterprise AI licenses, and governed integrations already live across our core systems.

We are looking for an Agentic AI Engineer to lead technical delivery-building connectors, agents, and workflows that transform our CRM, ERP, HRIS, and data platforms into a unified, natural-language-driven experience. This role will bring our AI strategy to life through real, production-grade systems.

Core Responsibilities
• Design and build agentic systems that orchestrate across ERP, CRM, data warehouse, HRIS, and BI platforms
• Develop multi-step AI workflows including tool selection, data retrieval, reasoning, and response generation
• Build and extend enterprise integrations, including authentication (OAuth, SSO) and RBAC enforcement
• Deliver AI-powered business solutions such as pricing engines, SDR automation, contract workflows, and executive dashboards
• Implement governance frameworks including audit logging, data lineage, and PII protection
• Partner with business teams to translate workflows into AI-enabled solutions
• Drive adoption through reusable prompts, tools, and training for non-technical users

What We're Looking For
• 3+ years building API integrations with CRM, ERP, or HRIS systems
• Strong Python experience with LLM APIs and SDKs
• Experience with agentic architectures (tool use, function calling, multi-step workflows)
• Familiarity with AI frameworks (LangChain, MCP, or similar)
• Experience with OAuth, SSO/SAML, and enterprise authentication
• Background in data platforms, BI tools, and enterprise data gove

Lead AI Engineer (Gen AI Platform, Agentic AI & LLM Infrastructure & Orchestration)

Overview

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:
• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
• Design, develop, test, deploy, and support AI soft