[Hiring] Agentic AI Engineer @Capgemini

Role Description

We are seeking a highly skilled Agentic AI Engineer to design, develop, and deploy intelligent AI agents using the Google Cloud Platform (GCP) AI ecosystem. The ideal candidate will leverage Vertex AI, Gemini models, Agent Builder, Vector Search, BigQuery, and Google Cloud services to create autonomous, goal-driven AI solutions that automate business processes, enhance customer experiences, and improve operational efficiency. The role requires expertise in Generative AI, Agentic AI architectures, Retrieval-Augmented Generation (RAG), orchestration frameworks, and enterprise-scale AI deployment. This role also requires experience with Automation testing.

• Lead the design, development, and deployment of enterprise-grade Generative AI and Agentic AI solutions on Google Cloud Platform (GCP) using Vertex AI.
• Architect and implement scalable Retrieval-Augmented Generation (RAG) solutions, including data ingestion, embeddings, vector search, and retrieval pipelines.
• Develop and optimize grounding and embedding strategies to improve AI response accuracy, relevance, and factual consistency.
• Build and manage Agentic AI and multi-agent systems capable of autonomous decision-making, orchestration, and task execution.
• Integrate Large Language Models (LLMs) with enterprise applications, APIs, and external tools using structured interaction frameworks such as Model Context Protocol (MCP).
• Design and deploy cloud-native AI applications leveraging Docker, Kubernetes, microservices, serverless technologies, and modern MLOps/CI-CD practices.
• Provide technical leadership through architecture reviews, proof-of-concepts (PoCs), solution design, troubleshooting, and delivery governance.
• Collaborate with cross-functional stakeholders and mentor engineering teams to drive AI innovation, best practices, and successful business outcomes.

Qualifications

• Strong hands-on experience with Google Cloud Platform (GCP), particularly Vertex AI, for building and deploying enterprise-scale Generative AI solutions.
• Proven expertise in designing and implementing Retrieval-Augmented Generation (RAG) architectures, including document ingestion, retrieval pipelines, and contextual response generation.
• Deep understanding of embeddings, vector databases, semantic search, and grounding techniques to improve AI accuracy, relevance, and trustworthiness.
• Extensive experience developing Agentic AI and multi-agent systems using modern frameworks such as LangChain and related orchestration technologies.
• Advanced programming skills in Python, with experience in enterprise application development using Java, C#, or Node.js.
• Strong knowledge of SQL and NoSQL databases, including data modeling, optimization, and integration with AI-driven applications.
• Experience building cloud-native and containerized applications using Docker, Kubernetes, microservices, and serverless architectures.
• Solid background in DevOps, CI/CD, MLOps, and AI model lifecycle management, ensuring scalable, reliable, and production-ready deployments.
• Excellent technical leadership, stakeholder management, problem-solving, and communication skills, with a proven track record of leading teams and delivering successful AI transformation initiatives.

Requirements

• Experience with Automation testing.

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.