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

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

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

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