Job Location : Whippany, NJ (Onsite/Hybrid from Day 1)

Job Description

We are seeking a Gen AI Engineer with deep expertise in the Microsoft AI ecosystem to design, develop, and deploy enterprise-scale AI solutions. The ideal candidate will have strong hands-on experience with Azure AI Services, Microsoft Copilot, Large Language Models (LLMs), RAG architectures, agentic AI frameworks, and production-grade AI implementations.

Key Responsibilities

• Design and develop enterprise Generative AI solutions using LLMs and multimodal AI models.
• Build and optimize Retrieval-Augmented Generation (RAG) architectures using vector databases and enterprise knowledge repositories.
• Develop intelligent agents and agentic workflows using frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, or CrewAI.
• Engineer prompts, guardrails, and evaluation frameworks to improve AI accuracy, reliability, and safety.
• Fine-tune, customize, and evaluate open-source and proprietary foundation models.
• Integrate AI solutions with enterprise applications, APIs, databases, Microsoft platforms, and business workflows.
• Develop scalable AI services and APIs for production environments on Azure.
• Establish AI governance, monitoring, security, compliance, and Responsible AI controls.
• Collaborate with architects, product managers, data scientists, and business stakeholders to deliver impactful AI solutions.
• Mentor junior engineers and promote AI engineering best practices across teams.

Required Skills

• 8+ years of software engineering experience with 3+ years focused on Generative AI.
• Strong experience with Azure AI Services, Azure OpenAI, Azure AI Foundry, and Microsoft Copilot.
• Hands-on experience building RAG-based applications and working with vector databases.
• Proficiency in Python and AI orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, or CrewAI.
• Experience deploying AI applications using Azure cloud services and modern DevOps practices.
• Strong understanding of prompt engineering, model evaluation, AI observability, and responsible AI principles.
• Experience integrating AI solutions with enterprise systems and APIs.

Preferred Qualifications

• Experience with Microsoft 365 Copilot, Copilot Studio, or custom Copilot development.
• Knowledge of MLOps, AI governance frameworks, and enterprise security standards.
• Azure AI, Azure Solutions Architect, or related Microsoft certifications.

The base compensation range for this role in the posted location is: 72786- 90273

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.

These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.

It is not typical for candidates to be hired at or near the top of the posted compensation range.

In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.

Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:

• 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