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,

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:

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,

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

GenAI / Agentic AI Engineer

Wilmington, DE - OPEN TO RELOCATION CANDIDATES

Hybrid: 3 days onsite
12-month contract (extension possible)
$68-70/hr W2 – NO CTC NO THIRD PARTY

Must be currently authorized to work in the U.S.

We are able to support H-1B transfer candidates, but are
unable to consider OPT/CPT candidates

Required Skills

3+ years experience in Generative AI / LLM / Agentic AI
Strong Python (must-have): APIs, async, microservices, distributed systems
Experience building RAG pipelines, embeddings, vector search, LLM orchestration
Experience with FastAPI / Flask
Hands-on GCP + Kubernetes/OpenShift
CI/CD + DevOps tooling experience
Experience working in enterprise or regulated environments
Ability to work independently and drive AI solutions
LangChain / LlamaIndex – nice to have -NOT REQUIRED

Day to Day

Build Generative AI and Agentic AI systems, including LLM-based autonomous agents and multi-agent workflows
Design and implement RAG pipelines (embeddings, vector search, retrieval, grounding, prompt engineering)
Develop LLM orchestration systems (function calling, tool use, guardrails, evaluation, safety controls)
Build Python-based AI microservices and APIs using FastAPI / Flask
Work on distributed AI systems supporting high-scale inference and retrieval workloads
Develop and manage MCP (Model Context Protocol) servers and context frameworks
Deploy AI solutions on GCP (Vertex AI, GKE, Cloud Run) and OpenShift/Kubernetes
Build and maintain CI/CD pipelines for AI services in enterprise environments
Work with vector databases (Pinecone, Redis, pgVector, MongoDB Atlas Vector Search, etc.)
Ensure security, governance, compliance, and responsible AI standards (banking environment)

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on 10/12/2026.

Work you'll do

As a Snowflake FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.

Partner with leaders, product owners, architects, and engineers to align priorities and delivery.

Lead working sessions to shape solutions and drive client outcomes.

Prototype and deliver working AI solutions using industry expertise and emerging capabilities.

Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.

Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.

Apply architecture decisions that balance quality, safety, latency, cost, and model risk.

Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.

Design extensible functionality, support sprint sizing, and align solutions with senior team members.

Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.

Company Summary

EchoStar is reimagining the future of connectivity. Our business reach spans satellite television service, live-streaming and on-demand programming, smart home installation services, mobile plans and products.Today, our brands include Boost Mobile, DISH TV, Gen Mobile, Hughes and Sling TV.

Department Summary

Our Technology teams challenge the status quo and reimagine capabilities across industries. Whether through research and development, technology innovation or solution engineering, our team members play a vital role in connecting consumers with the products and platforms of tomorrow.

Job Duties and Responsibilities

Candidates must be willing to participate in at least one in-person interview, which may include a live whiteboarding or technical assessment session.

EchoStar is seeking a Senior Engineer to lead the design, development, and deployment of advanced AI/ML and AI systems across enterprise applications. This role focuses on building scalable, production-ready AI solutions for real-time analytics, intelligent automation, and decision support systems. You will collaborate with cross-functional teams to ensure seamless integration of AI/ML technologies into cloud-native infrastructure while maintaining high standards of performance, reliability, and security.

Key Responsibilities:

Design and implement AI/ML systems and integrate with Generative AI technologiesCollaborate with the data science teams to integrate AI/ML solutions into cloud infrastructure, ensuring smooth transitions and knowledge continuityOptimize AI/ML pipelines for real-time data handling, scalability, and develop APIs for seamless system communicationImplement CI/CD pipelines with tools like GitLab and leverage cloud-native technologies for scalable AI solutionsConduct testing, benchmarking, and documentation to ensure AI/ML systems meet performance and functional requirementsLead AI/ML initiatives, mentor junior engineers, and contribute to roadmaps, aligning so

Job Description

Key Responsibilities

Design and implement AI-driven workflows to support and optimize the full course lifecycle, from curriculum structuring to final delivery
Build and maintain automation pipelines for curriculum outlining, content structuring, transcript processing, quiz generation, and multimedia workflows
Develop AI-assisted tools and backend systems to streamline course creation, learner support, and operational processes
Apply machine learning, natural language processing, and generative AI techniques to improve content quality, workflow efficiency, and scalability
Build and optimize data pipelines to handle educational content, including textual, video, and multimedia data
Develop analytics and reporting solutions to monitor learner engagement, workflow performance, and product effectiveness
Analyze data to identify inefficiencies, bottlenecks, and opportunities for optimization across course lifecycle workflows
Create dashboards and reporting systems to provide visibility into learner behavior, content performance, and operational metrics
Support and expand scalable AI-enabled workflows for multimedia content, including video, slides, and interactive formats
Design, develop, and maintain full-stack web applications (front-end UI + backend services) that operationalize AI workflows for course development and delivery teams
Build and document APIs and integrations (e.g., content systems, LMS tooling, analytics platforms), including authentication/authorization, observability, and error handling
Own the build, release, and deployment lifecycle for web services and applications, including CI/CD, environment configuration, and performance/security best practices
Collaborate with subject matter experts (SMEs), program teams, and stakeholders to translate requirements into practical technical solutions
Proactively identify and lead improvements across CPE workflows, taking ownership of automation initiatives and s

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

Miracle Software Systems, looking for a Generative AI Engineer to build cutting-edge AI applications powered by Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).

If you’re passionate about building scalable AI systems that combine enterprise data with modern cloud and APIs, this role is for you.

Required Skills:
• 8+ years of software engineering experience
• Strong Python expertise
• Hands-on experience with LLMs / Generative AI
• Experience building RAG systems
• Experience with vector databases (Pinecone, Weaviate, FAISS, etc.)
• Strong experience with FastAPI / REST APIs
• Solid knowledge of SQL & data processing
• Experience with GCP
• Familiarity with Git & Docker

What You’ll Do:
• Design and develop Generative AI applications using LLMs
• Build and optimize RAG pipelines using embeddings and vector databases
• Develop scalable REST APIs using FastAPI or similar frameworks
• Apply prompt engineering and model optimization techniques
• Build and manage data pipelines for AI systems
• Deploy solutions on Google Cloud Platform (GCP)
• Implement Docker-based deployments and CI/CD pipelines
• Collaborate with cross-functional teams to integrate AI into enterprise systems

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

Role: AI Agent Developer / Agentic AI Developer

Local to MN candidates (Onsite )

Role Summary

Design, build, and scale autonomous AI agents that augment software engineering, DevSecOps, and enterprise developer workflows using modern large language models (LLMs) and agentic architectures.

Key Responsibilities

Design and develop autonomous and semi autonomous AI agents leveraging LLMs and agentic frameworks to solve complex engineering and operational problems.

Build AI-powered developer productivity tools, including assistants for code generation, review, refactoring, and documentation.

Develop and deploy agents that automate coding, testing, CI/CD, DevSecOps, and quality assurance workflows.

Integrate leading LLM platforms and copilots (e.g., GitHub Copilot, Claude, Codex) into enterprise developer toolchains and workflows.

Architect agent orchestration, tool calling, memory, and feedback loops to ensure reliability, security, and scalability.

Partner with platform, security, and engineering teams to ensure secure, compliant, and production ready AI solutions.

Continuously evaluate emerging LLMs, frameworks, and agentic patterns to drive innovation and best practices.

Key Responsibilities Develop and maintain backend services using Core Java and Spring Boot. Integrate AI/LLM workflows into Java applications using frameworks like Spring AI. Design and consume RESTful APIs; familiarity with SOAP/WSDL/XML is a plus. Build and support event-driven systems using Kafka, JMS, and other messaging platforms. Collaborate on frontend development using frameworks such as React, Angular, or Vue. Implement observability tools for logging, metrics, and tracing. Contribute to CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes). Apply clean architecture principles and design patterns in system design. Participate in technical discussions, mentor team members, and collaborate across teams. Skill Metrics Restful APIs Docker Kubernetes Ai/LLM Java Spring Boot Required Skills 7–10+ years of experience in Java development and Spring ecosystem. Experience with AI/LLM integration in Java applications. Strong knowledge of REST APIs and event-driven architecture. Familiarity with frontend frameworks and responsive design. Experience with observability tools (Logback, Prometheus, OpenTelemetry). Proficiency in CI/CD, Docker, Kubernetes, and version control systems. Solid understanding of software design principles and architecture. Preferred Qualifications Experience with Spring Cloud and microservices components. Familiarity with vector databases (Pinecone, Milvus, Redis vector). Knowledge of domain-driven design, CQRS, and reactive programming (Spring WebFlux). Understanding of OAuth, JWT, and enterprise security protocols. Exposure to cloud-native AI deployments (AWS Lambda, Azure AI, Google Vertex AI). Experience with legacy system modernization and hybrid deployments. Knowledge of AI orchestration, prompt chaining, and multi-agent workflows. Experience with feature toggles, A/B testing, and canary deployments. Seniority level Mid-Senior level Employment type Contract Job function Engineering and Information Technology Industr

Security Clearance is required for this role

Job Title: AI/ML Engineer

Job Type: Full-Time

About Us:

micro1 is the end-to-end human data infrastructure behind AGI. Our AI recruiter model is used by frontier AI labs and Fortune 10s to source, vet, and deploy PhDs and professors from the world’s top universities at scale. These experts are placed directly into the training loops of the most advanced AI systems, powering the breakthroughs that move models forward. Our data platform converts their expertise into high-signal training datasets, and our talent management tooling measures, routes, and improves performance at scale.

Job Summary:

Join our team as a AI/ML Engineer and play a pivotal role in driving mission-critical government initiatives while also contributing to micro1’s proprietary AI infrastructure, you’ll harness advanced large language models (LLMs), retrieval-augmented generation (RAG), and multi-agent orchestration to deliver secure, scalable, and impactful machine learning systems. You’ll work closely with cross-functional experts, leveraging frontier AI platforms and the latest in agentic AI tooling.

Key Responsibilities:
• Design, implement, and optimize AI/ML models particularly leveraging LLMs, RAG, and prompt engineering for production grade applications.
• Develop and orchestrate multi-agent systems using frameworks such as LangGraph and LangChain.
• Integrate and deploy solutions on secure cloud environments, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
• Build robust data pipelines, manage ETL processes, and develop metadata catalogs and ontologies to ensure high-quality data for AI training and inference.
• Create and maintain REST APIs and SDK integrations to facilitate seamless data and model interactions.
• Collaborate with product, security, and engineering teams to ensure best-in-class delivery, following secure coding and DevOps best practices (CI/CD).
• Document technical decisions and communi

Security

AI Agent Engineer - Global Security Organization

Location
:

San Jose

Employment Type
:

Regular

Job Code
:

A118975

Responsibilities

The mission of TikTok's Global Security Organization is to build and earn trust by reducing risk and securing our businesses and products. Also known as "GSO", this team is the foundation of our efforts to keep TikTok safe, secure, and operating at scale for over 1 billion people around the world. We work to ensure that the TikTok platform is safe and secure, that our users' experience and their data remains safe from external or internal threats, and that we comply with global regulations wherever TikTok operates.

Trust is one of TikTok's biggest initiatives, and security is integral to our success. In whatever ways users interact with us — whether they're watching videos on their For You page, interacting with a Live video, or buying products on TikTok Shop — GSO protects their data and privacy, so they can have a secure and trustworthy experience.

The GSO provides industry-leading security and privacy services to Bytedance, guided by four principles: trust and transparency, business enablement, risk-informed decision-making, and proactive risk reduction. We strive to build sustainable, world-class security capabilities.

SecOps Validation Team (STOV) is responsible for the tools and technologies that support the TikTok infrastructure. STOV oversees technical validation, security operations, and drives engineering enhancements, including the deployment, configuration, and maintenance of security technologies across various domains.

STOV team is building domain specific AI applications to scale GSO's technical control compliance abilities. This role will work closely with STOV's product security to build AI agents which integrate with TikTok's CI/CD pipeline, providing TikTok product and development team with shift-left technical control review and implementation instructions.

As the

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

Chicago, Atlanta, Bridgewater, Southfield

AI/LLM Engineer

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 by a 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 organizations unlock 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 AI‑based testing environments, or strong interest with hands‑on exposure through projects or coursework.
• Working knowledge of at least one programming or scripting language such as Python (preferred), Java, or Java

About the Role:

Grade Level (for internal use):
12

S&P Global Corporate

The Role: Lead Workstation Agentic AI Engineer

The Team: Endpoint Management is part of the Digital Experience team. Our global team focuses on providing architectural and engineering services for S&P Global’s desktops, laptops, mobile devices, print services, and productivity applications.

What’s in it for you:

This position will provide an opportunity to expand your experience to all the technologies serviced by the Endpoint Management team and to work on state-of-the-art technologies used in the end-user computing space. You will work on projects and initiatives that will directly impact S&P Global’s employees and will expand your knowledge of our business and how Digital Experience’s technology enables the business.

Responsibilities:
• Architect and develop advanced vulnerability management solutions using Agentic AI frameworks and machine learning algorithms to automatically identify, prioritize, and orchestrate remediation workflows across enterprise workstation environments
• Design and implement automated CVE (Common Vulnerabilities and Exposures) response systems with real-time threat intelligence integration, including CVSS scoring automation and patch deployment orchestration
• Lead technical architecture decisions for endpoint security infrastructure, including integration with SIEM platforms, threat intelligence feeds, and enterprise security orchestration tools
• Develop comprehensive vulnerability assessment frameworks using PowerShell, Python, and REST APIs to interface with Microsoft Intune, Configuration Manager, and third-party endpoint management platforms
• Engineer advanced analytics and reporting solutions using data visualization platforms and business intelligence tools to provide executive-level vulnerability posture dashboards and risk metrics
• Establish DevSecOps practices for vulnerability management, including CI/CD pipeline integration, automated testing fr

Job Title: AI/ML Engineer

Job Type: Full-Time

Job Summary

Join our team as a AI/ML Engineer and play a pivotal role in driving mission-critical government initiatives while also contributing to proprietary AI infrastructure, you’ll harness advanced large language models (LLMs), retrieval-augmented generation (RAG), and multi-agent orchestration to deliver secure, scalable, and impactful machine learning systems. You’ll work closely with cross-functional experts, leveraging frontier AI platforms and the latest in agentic AI tooling.

Key Responsibilities
• Design, implement, and optimize AI/ML models particularly leveraging LLMs, RAG, and prompt engineering for production grade applications.
• Develop and orchestrate multi-agent systems using frameworks such as LangGraph and LangChain.
• Integrate and deploy solutions on secure cloud environments, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
• Build robust data pipelines, manage ETL processes, and develop metadata catalogs and ontologies to ensure high-quality data for AI training and inference.
• Create and maintain REST APIs and SDK integrations to facilitate seamless data and model interactions.
• Collaborate with product, security, and engineering teams to ensure best-in-class delivery, following secure coding and DevOps best practices (CI/CD).
• Document technical decisions and communicate complex concepts clearly to both technical and non-technical stakeholders.

Required Skills And Qualifications
• Proficiency in Python for AI/ML development, including experience with REST APIs and SDK integration.
• Hands-on experience with LLMs, RAG systems, and prompt engineering in production environments.
• Familiarity with multi-agent orchestration, tool use, and frameworks like LangGraph and LangChain.
• Deep understanding of cloud AI services (AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, AWS Bedrock).
• Background in building and maintaining data pipelines, ontologies, me

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Work you'll do

As an AWS AI&Data FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.

Partner with leaders, product owners, architects, and engineers to align priorities and delivery.

Lead working sessions to shape solutions and drive client outcomes.

Prototype and deliver working AI solutions using industry expertise and emerging capabilities.

Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.

Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.

Apply architecture decisions that balance quality, safety, latency, cost, and model risk.

Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.

Design extensible functionality, support sprint sizing, and align solutions with senior team members.

Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.

The team

AI & Engineering leverages cutti

We are looking for a driven AI Engineer to join our engineering team. In this role, you will focus on building, testing, and deploying autonomous AI agents and multi-agent systems. You will bridge the gap between traditional software engineering and modern Generative AI, working to enable LLMs (Large Language Models) to interact with external tools, APIs, and data sources.
• Equifax has a hybrid work schedule that allows for 2 days of remote work (Monday and Friday), with 3 days onsite (Tuesday, Wednesday, Thursday) every week.
• This role reports to our office in Alpharetta, Georgia
• This position does not offer immigration sponsorship (current or future) including F-1 STEM OPT extension support.
• This is a direct-hire role and is not open to C2C or vendors.

What you’ll do
• Design, develop, and operate high scale AI applications across the full engineering stack.
• Design, develop, test, deploy, maintain, and improve software that has AI / LLM integrations in it.
• Apply modern software development practices (serverless computing, microservices architecture, CI/CD, infrastructure-as-code, etc.)
• Work across teams to integrate our systems with existing internal systems, Data Fabric, CSA Toolset.
• Participate in technology roadmap and architecture discussions to turn business requirements and vision into reality. Participate in a tight-knit, globally distributed engineering team.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on network, or service operations and quality.
• Research, create, and develop software applications to extend and improve on Equifax Solutions. Manage sole project priorities, deadlines, and deliverables.
• Collaborate on scalability issues involving access to data and information. Actively participate in Sprint planning, Sprint Retrospectives, and other team activity

What experience you need
• Bachelor's degree or equivalent experience
• 5+ years of software engineering experi