AI Application Engineer (GenAI / RAG) Python

Capgemini • Burlington, MA

17d • Hybrid

About The Position

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.Job Description

Role Overview
As an AI Application Engineer, you will design, build, and deploy hands‑on GenAI applications that leverage LLMs, Retrieval‑Augmented Generation (RAG), and agent‑based workflows to support next‑generation Advisor Assistance and decision‑support tools.
This is a builder role focused on real-world GenAI systems, not research experiments or theoretical model work. Candidates are expected to demonstrate individual contribution, concrete design decisions, and outcomes from systems they have personally built.

Requirements

• Strong hands-on experience with Python in application development
• Practical experience building RAG systems (embeddings, vector databases, retrieval tuning)
• Experience working with LLMs (OpenAI, Anthropic, or similar)
• Familiarity with LangChain, LangGraph, or similar orchestration frameworks
• Experience deploying and operating applications in cloud environments

Nice To Haves

• Experience with agent-based systems or multi-agent workflows
• Knowledge of production monitoring, evaluation frameworks, and GenAI optimization techniques
• Prior experience working in regulated or enterprise environments

Responsibilities

• Design and implement RAG-based applications, including embeddings, vector search, and retrieval strategies
• Build LLM-powered services using Python that integrate with internal systems and APIs
• Develop conversational and advisor-assist interfaces backed by LLM orchestration and tool usage
• Implement agentic workflows (tool execution, routing, memory, task planning) using frameworks such as LangChain or LangGraph
• Design prompt structures, system instructions, and interaction patterns focused on reliability and grounded responses
• Implement evaluation strategies for retrieval quality, answer faithfulness, and hallucination mitigation
• Optimize latency, cost, and relevance across GenAI pipelines
• Integrate structured and unstructured data sources including databases, APIs, enterprise systems, and document repositories
• Build ingestion pipelines and data preparation workflows to support GenAI use cases
• Package and deploy services using containers, APIs, and CI/CD pipelines
• Apply monitoring, logging, security, and testing best practices
• Ensure compliance with Responsible AI, security, privacy, and data governance standards

Benefits

• Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
• Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs
• Other benefits as provided by local policy and eligibility

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed