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,

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,

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,

BPX GenAI Squad Data Scientist requirement

Data Scientist AIML P2P3

Experience 6- 8 Years

Skillset Required

Expert level understanding of Machine LearningDeep Learning concepts techniques algorithms

Hands on working experience on building end to end MLDL solutions

Expert level proficiency in Python programming is a prerequisite

Strong understanding of objectoriented programming and design principles

Experienced with common data science packages in Python like Pandas Numpy Matplotlib and frameworks such as Tensorflow Pytorch

Handson experience in RESTful APIs development with FlaskAPI FastAPI

Excellent understanding of NLP concepts libraries including Word2Vec TFIDF NLTK SpaCy Gensim BERT GloVe etc

Must have experience in development of NLPNLGNLU projects

Deep understanding of Transformer Architectures including BERT GPT DistillBert

Good understanding of Generative AI concepts like Large Language Models Finetuning Evaluating LLMs PEFT RAG Embeddings Vector Databases etc

Experience in frameworks such LangChain LlamaIndex

Experience with Large Language models such as Llama GPT PaLM etc

Experience with Amazon Bedrock Azure OpenAI GCP GenAI Studio

Expertise in training and finetuning LLMs would be preferred

Proficientcy in model development deployment and optimization techniques

Certifications in GenAIAIML preferred

Experienced in deploying AI solutions in cloud environments

Working knowledge in any of the major cloud services AWSAzure

Working knowledge in either of AWS SageMakerAzure Cognitive ServicesGoogle Vertex AI

Certification in any of the Cloud Platforms AWSAzureGCP

Good problemsolving and critical thinking skills

Familiarity with version control systems Git

Knowledge of SQL NoSQL

Key Roles Responsibilities

Create and maintain highquality reusable code components and libraries for future use

Perform rigorous testing and validation to ensure models perform accurately and efficiently in various conditions

Sr. AI Engineer – Agent Orchestration

A high-growth technology company building AI-powered software for US government customers is hiring a Senior AI Engineer focused on agent workflow orchestration. The company’s AI agent has seen rapid adoption, and the team is now pushing it to handle increasingly complex, multi-step tasks either fully autonomously or in a human-in-the-loop mode.

This role is squarely backend and systems-focused. You’ll be designing how an AI agent plans, sequences, and executes long-running workflows — coordinating across multiple tools, data sources, and sub-agents to complete jobs that today require hours of manual work. Think of it as building the brain and nervous system of the agent, not the hands.

What You’ll Do

Architect and build the workflow engine that powers multi-step agent task execution — including planning, sequencing, branching, error recovery, and human handoff pointsDesign and implement multi-agent coordination patterns: routing between specialized sub-agents, managing shared memory and context, and orchestrating parallel workstreamsBuild scalable tool-use infrastructure that lets agents dynamically discover, select, and chain tools based on task requirementsOwn reliability and observability for long-horizon agent tasks — designing checkpointing, retry strategies, and evaluation harnesses that catch failures before users doDefine and enforce the technical architecture and engineering standards for agentic systems across the platform

What We’re Looking For

You have built an LLM reliably completing complex, multi-step tasks in production — not just single-turn Q&A, but real workflows with branching logic, tool calls, and failure handlingDeep experience with workflow orchestration patterns (DAGs, state machines, event-driven architectures) applied to LLM-powered systemsHands-on experience with agent frameworks (Claude Agent SDK, OpenAI Agent SDK, LangGraph, or similar)Strong understanding of LLM reliability e

Company Description

Govini transforms Defense Acquisition from an outdated manual process to a software-driven strategic advantage for the United States. Our flagship product, Ark, supports Supply Chain, Science and Technology, Production, Sustainment, Logistics, and Modernization teams with AI-enabled Applications and best-in-class data to more rapidly imagine, develop, and field the capabilities we need. Today, the national security community and every branch of the military rely on Govini to enable faster and more informed Acquisition decisions.

Job Description

We are seeking an experienced Lead AI Engineer to lead our Agentic AI team as we scale our agentic offerings across all levels of the US government. Over the past year, we have seen the rapid adoption of our agent, Ace. We expect Ace to be handling much more complex tasks and workflows end-to-end and/or in cooperation with a human user as time goes on. The team is striving to make Ace an even more effective agent, focusing on planning, reliable execution over longer time horizon tasks, scaled tool use, Ace Skills, memory, and inter-agent coordination.

In order to do this job well, we are looking for someone who can demonstrate a project built on LLMs that showcases your skill at getting them to do complex tasks.

Experience leading agentic system development from ideation through production, including technical design, architecture decisions, and day-to-day leadership of Data Scientists and Machine Learning Engineers
Experience integrating and working with LLMs, with a strong understanding of their capabilities and limitations
Experience integrating and working with agent frameworks like Claude Agent SDK or OpenAI Agent SDK
Experience building observability, evaluation, and feedback loops for agent behavior (telemetry, prompt evaluation, regression testing, and reliability metrics).
Experience working in highly ambiguous environments, and operating with

We are hiring senior engineers who build fast, think AI-first, and can take agentic AI from prototype to production. You will design, ship, and operate agentic systems that combine large language models (LLMs), tools/functions, planning, memory, evaluation, and multi-agent communication. You will work primarily in Python for AI services and integrate with our enterprise stack (TypeScript/Angular, .NET/C#, SQL Server, Azure), delivering trustworthy, cost-efficient, low-latency experiences in real customer workflows.

What You'll Do!
Build agentic AI applications on Azure AI Foundry: Azure OpenAI models, Prompt Flow, tools/function-calling, evaluations, vector search (Azure AI/Cognitive Search), and orchestration for multi-step reasoning and tool use.Design memory & grounding: implement episodic/semantic/long-term memory with vector/graph stores; architect RAG pipelines and retrieval strategies that improve factuality and reduce latency/cost.Integrate via Model Context Protocol (MCP) to standardize tool/skill access; design agent-to-agent communication, delegation, and event-driven workflows.Connect agents to Microsoft Fabric (OneLake, Lakehouse, Warehouse, Real-Time Analytics) and Dataverse entities/workflows; ensure lineage, governance, and auditability.Develop AI-native backend services in Python (FastAPI, asyncio) with evaluation harnesses, observability, and cost/latency/quality dashboards.Embed AI features into the MTech stack: TypeScript/Angular UIs, .NET/C# services, SQL Server, NServiceBus, Azure DevOps pipelines, and Ionic/Cypress where applicable.Use AI-augmented development tools like GitHub Copilot, Bolt, Cursor, Replit, and vibe-coding workflows to accelerate delivery, test generation, refactoring, and documentation.Implement safety & reliability: guardrails, red-teaming, PII protection, prompt hardening, regression tests, automated evaluations; uphold SLO/SLA excellence in production.Implement full cycle agentic engineering: design → model/tool selecti

HiHope you are doing well

This is Bhanu from Intellectt INC; we have an immediate opportunity with one of our clients. Please find the below job description and if you are interested, please forward your resume to bhanuprakash@intellectt.com

Position: Agentic AI Engineer (Python)
Location: Atlanta, GA – Onsite
Duration: Long Term

Job Description:

We are seeking an experienced Agentic AI Engineer to design and implement intelligent systems leveraging autonomous agents, LLMs, and advanced Python frameworks. The ideal candidate will have hands-on experience developing agentic AI solutions that can plan, reason, and act using multi-agent orchestration and modern AI toolkits.

Key Responsibilities:

Design and build agentic AI frameworks and intelligent workflows using LLMs.Develop and integrate Python-based AI applications with internal systems and APIs.Utilize tools such as LangChain, CrewAI, AutoGen, or OpenDevin for agent orchestration.Build AI pipelines that can autonomously perform reasoning, decision-making, and task execution.Collaborate with cross-functional teams to align AI initiatives with business goals.Optimize AI agents for scalability, performance, and accuracy in production environments.Stay current with advancements in LLMs, agentic AI, and generative AI ecosystems.Required Skills & Experience:

Strong programming skills in Python and familiarity with AI/ML frameworks.Proven experience developing LLM-driven or multi-agent AI systems.Hands-on experience with LangChain, AutoGen, CrewAI, or related frameworks.Knowledge of OpenAI, Anthropic, or AWS Bedrock APIs.Experience with prompt engineering, retrieval-augmented generation (RAG), and vector databases (e.g., FAISS, Pinecone, Chroma).Strong problem-solving and analytical skills.Excellent communication and teamwork abilities.Nice to Have:

Experience in healthcare or insurance domain.Familiarity with cloud platforms (AWS, Azure, or GCP) for deploying AI models.Exposure to MLOps or AI agent lifecycle ma

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

Job Title: AI Agent Engineer

Location: Reston, VA ( Onsite)

Job Description:

Required Skills:

Strong experience in AI/ML concepts and model development

Hands-on experience with Large Language Models (LLMs)

Experience with OpenAI API or similar AI platforms

Good understanding of RAG architecture and implementation

Experience with embeddings and vector databases (e.g., Pinecone, FAISS, Weaviate)

Proficiency in Python or Go (Golang)

Experience with AWS services (EC2, S3, Lambda, SageMaker, etc.)

Knowledge of REST APIs and microservices architecture

LLM Engineer
12 month+ contract
100% Remote

Position Summary

Position Summary
The LLM Engineer is responsible for designing, developing, and deploying large language model solutions that support enterprise operations. This role focuses on Azure AI services, Azure OpenAI, and the integration of LLM capabilities into internal applications and workflows. The engineer will work closely with cross-functional teams to turn business requirements into scalable, production-ready AI solutions.

Key Responsibilities
• Design, develop, and deploy LLM-based applications using Azure AI, Azure OpenAI, and related cloud services
• Build retrieval-augmented generation (RAG) pipelines, embeddings, vector stores, and prompt workflows
• Integrate LLM capabilities into enterprise platforms such as Power Platform, Microsoft 365, and internal systems
• Prepare, clean, and transform data for LLM consumption and build feature and inference pipelines
• Implement model monitoring, lifecycle management, evaluations, and performance tuning
• Collaborate with automation engineers, product owners, and business stakeholders to assess and scope use cases
• Document solution architectures, model workflows, and technical designs
• Evaluate emerging AI tools, frameworks, and best practices
• Support troubleshooting, testing, and responsible AI standards

Required Skills and Experience
• Strong hands-on experience with Azure AI services, Azure OpenAI, or similar LLM platforms
• Proficiency in Python and common ML libraries (scikit-learn, pandas, PyTorch, TensorFlow)
• Practical experience building and deploying LLM applications, including embeddings, RAG, prompt engineering, and fine-tuning
• Understanding of data pipelines, model evaluation, and monitoring
• Experience integrating LLM solutions into enterprise systems
• Ability to communicate complex AI concepts clearly to both business and technical stakeholders

Preferred Experience
• Exposure to Power Platform AI Builder, Copilot Studio, or Micro

Company Description
Lumen Solutions Group Inc. is a technology consulting Services company based in Florida. We provide a wide array of experienced business and IT professionals supporting clients from solution design to implementation and support. We specialize in professional IT consulting services, IT Staffing, Business/IT Strategy, Business Process Blueprints, Enterprise Architecture, Enterprise Transformation.

Role: AI Agent Engineer / Agentic AI Engineer
Location: Austin, TX (Hybrid - On Site and Telework)
Job Type: Contract

Note: We need only Local Texas Candidates.

Job Summary:
We are seeking an experienced AI/ML Engineer / Autonomous Agent Engineer with 8+ years of hands-on experience in artificial intelligence, machine learning, and advanced data science to design, develop, and deploy production-grade autonomous AI agents and intelligent workflows. The ideal candidate will have a proven track record of building scalable, enterprise-ready AI solutions, including multi-agent systems, agentic workflows, and Retrieval-Augmented Generation (RAG) architectures using vector databases. This role requires deep expertise in context engineering, LLM orchestration frameworks such as LangChain, LangGraph, CrewAI, or AutoGPT, and strong proficiency in Python along with leading AI/ML libraries and platforms including OpenAI, Hugging Face, and Azure AI.

Required Skills

4+ years of experience in AI/ML engineering or advanced data science. 4+ years of proven track record of building and deploying production-grade autonomous agents. 4+ years of strong experience in context engineering. 4+ years of deep experience with LangChain, LangGraph, CrewAI, or AutoGPT. 4+ years of experience implementing RAG architectures using vector databases. 4+ years of proficiency in Python and AI/ML libraries (OpenAI, Hugging Face, Azure AI). 4+ years of experience integrating LLMs via APIs. 4+ years of knowledge of AI governance, model lifecycle management, and evaluation. 4+ years

We're Celonis, the global leader in Process Intelligence technology and one of the world's fastest-growing SaaS firms. We believe there is a massive opportunity to unlock productivity by placing AI, data and intelligence at the core of business processes - and for that, we need your help. Care to join us?Role Description
As an Applied AI Engineer specializing in the Public Sector, you are pushing the envelope in solving critical operational challenges for State and Local Government agencies. You will be working with our most strategic public sector clients, understanding their unique objectives—from enhancing citizen services and modernizing legacy systems to optimizing grant management and regulatory compliance—and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with top AI and ML technology partners, such as Microsoft, OpenAI, and Databricks.With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands the complex realities of government operations (breaking down agency silos) and enables agencies to industrialize AI. This unlocks real ROI on AI deployments, maximizing taxpayer value at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to government CIOs and Agency Directors, and ensure successful implementation, adoption, and value realization to increase the footprint of Celonis across state and local governments.
Key Responsibilities:

AI Discovery & Solutioning: Understand public sector AI strategies and specific agency challenges (e.g., benefits administration backlogs, procurement bottlenecks, public safety resource allocation, or permitting delays). As a Celonis product and government domain expert, find the best problem-solution fit and translate agency requirements into innovative solutions that deliver measurable public impact.

Pre- and Post-Sales Execution: Actively drive the full customer lifecycle within the publi

• *Title: Application Security (AppSec) + AI Engineering
• *Location: Iselin, NJ (Main) and other Cyber prime locations like Minneapolis, MN, Chander AZ, Dallas, TX (Los Colinas), Charlotte, NC
• *Duration: 6 Months Contract with Possible Ext.
• *Onsite Expectation: 3 days/week (Tuesday–Thursday)
• *JD:
• *Core focus:
• *Application Security (AppSec) + AI Engineering
• *Strong Application Security background

Hands-on with AppSec tools like:
• Checkmarx (critical)
• Other SAST/DAST tools

AI-driven Code Security & Remediation (production-level experience)
• Using AI to:
• Auto-generating secure code fixes
• Detect vulnerabilities
• Generate code remediation suggestions
• Integrating AI into security workflows

Tools / Platforms
• OpenAI (PRIMARY focus)
• GitHub Copilot
• Cloud-based AI coding tools

Real Use Cases Expected
• Deploying AI tools within AppSec pipelines
• Integrating AI with tools like Checkmarx
• Automating vulnerability remediation
• Improving developer productivity using AI

Required Tech Stack
• Python
• Exposure to TensorFlow / PyTorch
• Experience with:
• JIRA (tracking)
• Confluence (documentation)
• True Engineer background required

AppSec Tools and AI tooling
• Focus on AppSec AI eng. Deploying AI toolsto complement existing Appsec tools like Checkmarx and Black Duck
• experience in deploying AI tools for AppSec processes, including auto code remediation.
• The role requires experience with models like Copilot, OpenAI, and Entropic Cloud for code remediation.
• Candidates should have production experience implementing AI tools at scale, not just proof of concept (POC) code.
• The role is specific to AppSec AI engineering, not traditional AI engineering roles.
• role involves writing frameworks against AI models to remediate Checkmarx findings, not directly working with Checkmarx queries.
• various AI models.
• *--------
• *Thanks.
• *Regards,
• *Ashish
• *Email ID: ashish@Hireontech.com**

GAP INTERNATIONAL – A unique, purpose-driven, consulting company

ABOUT GAP INTERNATIONAL

Gap International is a global consulting firm that partners with executives to achieve breakthrough business results. We're a team of passionate problem-solvers committed to innovation and transformation. As part of our growth strategy, we're expanding our AI capabilities to deliver cutting-edge solutions across the enterprise. This role offers the opportunity to work on impactful projects, including dialog-driven learning and business process acceleration.

ABOUT THE ROLE

You will be part of a tight knit, highly collaborative research and development team focused on building real-world AI applications. As an AI/LLM Engineer, you will lead the design and implementation of advanced systems centered on large language models and natural language understanding. Your work will involve techniques such as fine-tuning, retrieval-augmented generation (RAG), and prompt engineering to solve meaningful business challenges.

You will work closely with teams to explore data, shape requirements, and integrate AI capabilities into internal tools and digital products. Your contributions will drive innovation and shape transformative projects across the organization.

RESPONSIBILITIES

Design and implement AI systems using Large Language Models (LLMs) to solve enterprise challenges and improve operational efficiency.
Fine-tune foundation models and apply techniques such as retrieval-augmented generation (RAG) and prompt engineering.
Collaborate with cross-functional teams to integrate AI capabilities into internal tools, workflows, and digital products.
Evaluate and experiment with frameworks and tools like Hugging Face, LangChain, OpenAI, Claude, and LLaMA.
Build and deploy scalable LLM solutions across cloud-based and local environments, leveraging container orchestration tools where applicable.
Lead architectural decisions and guide implementation o

Our client is a world-renowned biotech powerhouse, but they're currently operating with the speed and ambition of a startup in the AI space. We aren't just looking for someone to build chatbots; we need a Senior Agentic AI Modeler who can architect systems that actually reason, plan, and solve complex problems autonomously.

If you’re obsessed with the 'bilingual' intersection of traditional predictive modeling and the new frontier of Multi-Agent orchestration (and you've already started playing with MCPs), we should talk.
• You'll have the freedom of a heavily remote schedule, with the added benefit of joining the team in the office roughly once a week (about 5 days a month) to stay connected.

About the Role:

Agentic System Design & Development
• Architect and implement autonomous and semi-autonomous agent workflows using modern frameworks (LangChain, OpenAI Assistants, Semantic Kernel, LlamaIndex, CrewAI, DSPy, etc.)
• Build agents capable of multi-step reasoning, task decomposition, planning, and tool execution.
• Develop tooling ecosystems—function APIs, retrieval endpoints, evaluators, monitoring hooks—for agent orchestration.
• Prototype, fine-tune, and optimize LLMs, RAG systems, and multi-agent architectures for reliability and low hallucination rates.

Modeling & Prompt Engineering
• Create robust prompt pipelines, templates, and routing strategies for diverse commercial/analytics use cases.
• Optimize agent behaviors via prompt distillation, chain-of-thought design, system message tuning, guardrails, and evaluation frameworks.
• Use datasets and logs to refine agent behavior through supervised fine-tuning or RLAIF where applicable.

Solution Integration & Delivery
• Integrate agents with enterprise systems, APIs, data stores, CRMs, search tooling, and business applications.
• Implement observability for agent decision-making: trace logs, tool call audits, success/failure rates, safety events, drift.
• Partner with engineering and MLOps to deploy agentic

DeVry University strives to close our society’s opportunity gap and address emerging talent needs by preparing learners to thrive in careers shaped by continuous technological change. Through innovative programs, relevant partnerships, and exceptional care, we empower students to meaningfully improve their lives, communities, and workplaces.

Our colleague experience is an area of obsessive focus. At DeVry University, we care about you. Because, only through you can we deliver our unique Care Formula to our learners and partners.

Overview

The Applied AI Prompt Engineer designs, optimizes, and maintains the prompts, agent behaviors, context structures, and Retrieval-Augmented Generation (RAG) workflows that power DeVry’s enterprise AI ecosystem—including Copilot, ChatGPT, agentic workflows, and internal knowledge tools.

This is a hybrid role blending prompt engineering, operational AI lifecycle management, and cross-functional collaboration. You will rapidly prototype prompt variations, run evaluations, maintain knowledge pipelines, and ensure outputs remain accurate, compliant, and aligned with DeVry’s tone and policies.

The ideal candidate is fast, curious, experimental, and skilled at translating human-to-human support scenarios into reliable AI-driven interactions.

Key Responsibilities

Prompt Design & Optimization
• Design and maintain high-quality prompts, and agent instructions for enterprise AI platforms.
• Rapidly prototype and iterate prompt variants using structured experimentation, evaluation metrics, and A/B testing.
• Build evaluation rubrics, structured test cases, and prompt datasets to measure accuracy, tone, consistency, and policy alignment.
• Adapt prompts for higher-education use cases (e.g., advising, HR, faculty support, IT, student services) while maintaining institutional tone and compliance.

RAG & Knowledge Integration
• Curate and manage document ingestion, embeddings, and knowledge base updates to ensure relevant, current, and contex

At Lawyer.com, we are revolutionizing how people connect with leading legal professionals. We are looking for an exceptional builder to join our team in a fast-paced environment.

But we are not looking for a traditional engineer who stares at a blank screen and writes code by hand. We are hiring a Model Jockey.

Your job is to build and deploy AI-powered applications, voice solutions, and text agents that drive real business value. You will act as an orchestrator, steering multiple AI instances in parallel to write code, review architecture, and automate complex workflows. You will direct the models, shape their output, catch their mistakes, and ship products faster than a traditional engineering team ever could.

Requirements

Core
• 3 years of Model Jockey experience. (Read here for a definition of a Model Jockey: https://medium.com/@rybeswick/heads-up-knowledge-workers-your-last-job-is-model-jockey-974edf9c1b60)
• Bachelor's degree in Computer Science, AI, or a related field.
• Systems-Level Engineering Instincts: We do not care what specific languages or frameworks you have memorized. We care that you understand underlying architecture, logic, and data flow. You will not be fixing code by hand. Instead, you need the engineering instincts to spot when a model is taking the wrong approach and the ability to rapidly direct the AI to debug and correct its own work in any stack.
• Technology-Agnostic Mindset: You are wired to figure things out. If a project requires a new database, API, or cloud environment, you do not spend weeks reading documentation. You spin up an agent, give it the context, and start building immediately.
• Parallel Orchestration: Proven ability to run multiple AI agents (like Claude Code, OpenAI, GitHub Copilot) simultaneously without losing the thread.
• Strategic Inquiry and Prompting: Knowing how to ask the right questions to pull the best work out of models, creating effective workflows for complex tasks, and optimizing for accuracy.
• Hum

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 strong foundation in building cloud-native solutions and hands-on experience designing and deploying agentic systems, especially for enterprise environments. You’re a critical thinker who thrives in ambiguity, delivering concrete results by designing, building, and running AI agents that augment workflows and scale across modern infrastructure.

You'll shape how enterprises adopt AI-native engineering - either by leading complex agentic solutions and developing engineering talent, or by owning critical technical areas end-to-end as a senior IC

The Work

You’ll partner directly with client stakeholders — 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 net-new platforms and systems that need to be stitched together in our clients’ environments alongside our ecosystem partners.

Agent Architecture & Engineering
• Design and build enterprise-ready AI agents incorporating retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.
• Implement resilient, testable, and maintainable agentic workflows that can be iterated on quickly.

AI Platform Integration
• Develop and/or extend abstraction layers across AI providers (Anthropic, Google, OpenAI, etc.) to enable seamless integration and multi-provider enablement.
• Contribute to shared libraries, SDKs, and patterns that can be reused across clients.

Cloud-Native Engineering
• Leverage containerization (Kubernetes, Dock

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:

A Forward-Deployed AI Engineer who thrives at the intersection of cutting-edge AI platforms, enterprise systems, and real-world business problems. It is a product-minded, customer-embedded engineering role where you will work directly with clients, partners, and internal product teams to design, prototype, deploy, and scale end-to-end AI solutions.

The Work:

You will work hands-on with platforms such as OpenAI, Anthropic, ServiceNow, and other enterprise systems, translating ambiguous business needs into production-grade AI workflows that deliver measurable impact.

This role requires strong engineering depth, excellent communication, comfort with ambiguity, and a builder’s mindset.

Responsibilities:

Work directly with clients and internal teams to understand business problems, shape AI use cases, and define technical solutions — often from ambiguous or evolving requirements.

Design and implement end-to-end AI solutions, integrating LLMs and AI services (OpenAI, Anthropic, etc.) with enterprise platforms (ServiceNow, Salesforce, data platforms, internal systems).

Rapidly prototype, iterate, and deploy AI-enabled workflows, agents, copilots, and automations into real operational environments.

Serve as the technical bridge between product, engineering, data, and business stakeholders, ensuring solutions are technically sound, usable, and aligned with business value.

Drive solution architecture, including:

Prompt and workflow design

API integrations and orchestration

Enterprise knowledge integration)

Security, privacy, and governance considerations

Own solutions from concept → prototype → production → iteration, with acco