Senior GECX AI Forward Deployed Engineer - Lead Software Engineer

Capgemini•Chicago, IL

22h•Hybrid

About The Position

Capgemini is hiring an experienced software development professional to design, build, and support production-grade conversational and Agentic AI applications. The role involves hands-on development with Python, APIs, JSON, Gemini, Vertex AI, Google ADK, and relevant agent frameworks, as well as building CES/GECX integrations and modernization scenarios. The engineer will develop agent workflows, tool/function calling, orchestration, state and context management, and RAG and enterprise-grounding solutions. The role also includes integrating agents with enterprise systems, implementing security and authentication, deploying applications on GCP, and establishing evaluation, tracing, observability, guardrails, and regression testing. The engineer will work directly with customer engineering teams to prototype solutions, debug implementations, diagnose production issues, and resolve technical blockers. This is a hybrid role based across Atlanta, Nashville, Chicago, Dallas, Houston, and New Jersey. The posted base compensation range is $117,930–$223,591. Eligible regular, full-time employees may receive a benefits package that includes paid time off, holidays, personal days, sick leave, medical, dental and vision coverage, retirement savings plans, life and disability insurance, and employee assistance programs, subject to local policy and eligibility.

Requirements

15+ years of relevant experience as a Lead or Architect.
Strong hands-on Python and software engineering skills.
Good experience in Gemini/Generative AI application development, Vertex AI, and Agentic AI architectures.
Solid exposure to REST APIs and JSON.
Experience in RAG, embeddings, and enterprise grounding.
Experience with GCP application deployment, IAM/security fundamentals, and enterprise integration.

Nice To Haves

Experience with Google ADK and CES/GECX.
Contact-center/CCaaS integration experience.
Experience with multi-agent architectures, MCP, and A2A.
Experience with agent evaluation and observability.
Experience with streaming/real-time APIs, production conversational AI, and telephony integrations.

Responsibilities

Design and build production-grade conversational and Agentic AI applications.
Develop solutions using Python, APIs, JSON, and modern software engineering practices.
Build and troubleshoot CES/GECX integrations and modernization scenarios.
Build agents using Gemini, Vertex AI, Google ADK, and applicable agent frameworks.
Implement tool/function calling, workflows, state and context management, and agent orchestration.
Develop RAG and enterprise-grounding solutions over structured and unstructured data.
Integrate agents with enterprise APIs, databases, CRM, contact-center platforms, and backend systems.
Develop full-stack components needed to complete customer solutions.
Implement secure authentication, IAM, secrets management, and service-to-service communication.
Deploy applications using appropriate GCP services.
Implement agent evaluation, tracing, observability, guardrails, and regression testing.
Diagnose production issues across agent logic, prompts, retrieval, tools, APIs, infrastructure, and distributed services.
Rapidly prototype technical solutions and develop validated prototypes toward production readiness.
Work with customer engineering teams to reproduce issues, debug implementations, and resolve technical blockers.

Benefits

Paid time off, including vacation of 12–25 days depending on employee grade, company-paid holidays, personal days, and sick leave, subject to policy.
Medical, dental, and vision coverage, or provincial healthcare coordination in Canada.
Retirement savings plans, such as 401(k) in the U.S. or RRSP in Canada.
Life and disability insurance.
Employee assistance programs.
Other benefits as provided by local policy and eligibility.

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