Capgemini

Gen AI Lead (ME)

Posted On

Jan. 6, 2026

Location

Bangalore, Karnataka

Experience Level

Executives

Job Type

Permanent

Apply By

Feb. 25, 2026

Job Description

We are seeking a hands-on AI Technical Leader with deep expertise in Generative AI and Agentic AI to spearhead the design, development, and delivery of next generation AI platforms and products. This role combines technical leadership, presales excellence, DevOps know-how, and executive presence. The successful candidate will be equally comfortable writing production-grade code, leading engineering teams, and presenting transformative AI solutions to C-level executives.

You will play a pivotal role in building modern AI platforms, driving innovation and delivery excellence, and winning strategic deals by shaping and articulating compelling AI-led solutions.

Primary Skills

Key Responsibilities
Technical Leadership & Delivery
- Lead end-to-end delivery of sophisticated AI platforms and products, ensuring scalability, reliability, and performance.
- Build and mentor cross-functional teams of developers, data scientists, and ML engineers.
- Define architectural blueprints, enforce engineering best practices, and champion responsible AI principles.
- Stay ahead of emerging AI trends and ensure solutions leverage the latest frameworks and platforms.
Hands-on Development
- Actively design, code, and deploy production-grade AI solutions using Python (and familiarity with Java/Scala).
- Build, fine-tune, and operationalize Large Language Models (LLMs) across OpenAI (GPT models), Anthropic (Claude), Google Gemini, Meta LLaMA, Falcon, and Mistral.
- Apply advanced frameworks and libraries such as LangChain, LlamaIndex, Hugging Face Transformers, and RAG (Retrieval-Augmented Generation) architectures.
- Agentic Frameworks & MCP Integration (critical focus)
- Autonomous & Multi-Agent Systems: Develop AI agents and multi-agent architectures that orchestrate tasks, collaborate, and divide work for complex workflows.
- MCP Server Integration: Build and deploy Model Context Protocol (MCP) servers to expose tools and data, enabling agents to interact with external systems and databases.
- Agentic Framework Expertise, Standardized Interfaces, Multi-Agent Systems, Deep Understanding of Agentic Frameworks
Platforms & Infrastructure
- Deploy AI workloads on enterprise-grade platforms
- Architect AI/ML pipelines with Kubernetes (K8s), Docker, Terraform, and GitHub Actions for CI/CD.
- Integrate vector databases (Pinecone, Weaviate, Milvus, ChromaDB, Redis Vector Search) and knowledge graphs (Neo4j) into scalable production systems.
- Ensure data pipelines leverage Delta Lake, BigQuery, Elasticsearch, and other modern data architectures.
DevOps, CI/CD & Testing
- Implement modern DevOps practices, ensuring automation, scalability, and high availability of AI solutions.
- Design and maintain CI/CD pipelines for rapid deployment of AI models and services.
- Apply LLM testing, evaluation, and monitoring techniques (including Deepeval, unit/integration testing for AI agents, and benchmark validation).
- Monitor model drift, performance, and safety using best-in-class tools.
Presales & Client Engagement
- Act as a trusted advisor during pre-sales engagements, helping shape AI strategies and solutions tailored to client needs.
- Author and present winning proposals, RFP responses, and solution blueprints that differentiate our offerings.
- Collaborate closely with sales teams to drive business growth, influencing C-level and senior decision-makers.
- Deliver thought leadership through workshops, demos, and speaking engagements at industry forums.
Executive Presence & Leadership
- Represent the company in senior executive discussions, client boards, and industry panels.
- Translate highly complex AI concepts into business-impact storytelling that resonates with non-technical leaders.
- Inspire confidence, build long-term relationships, and establish the organization as a leader in enterprise AI

Skills and Experience

15+ years in technology leadership with at least 5 years in AI/ML solution delivery.
Proven track record in Generative AI, Agentic AI, and AI product development.
Deep coding expertise in Python, with ability to prototype and deliver production-ready solutions
Hands-on experience with LLMs, AI agent frameworks, RAG architecture, and MCP-based systems.
Expertise in agentic frameworks (LangChain, LangGraph, etc.) and multi-agent system design.
Strong knowledge of cloud-native AI/ML platforms (Azure, AWS, GCP) and MLOps.
Mastery in DevOps, CI/CD pipelines, and AI testing/evaluation frameworks (e.g., Deepeval)
Successful presales background with proposal writing, solutioning, and client engagement.
Exceptional presentation, communication, and executive stakeholder management skills.

Nice-to-Have

Experience with responsible AI, governance, and compliance frameworks.
Exposure to multi-modal AI (text, image, audio, video).
Prior experience working in consulting or client-facing delivery roles.
Contributions to open-source AI frameworks or published research in AI/ML.

15+ years in technology leadership with at least 5 years in AI/ML solution delivery.
Proven track record in Generative AI, Agentic AI, and AI product development.
Deep coding expertise in Python, with ability to prototype and deliver production-ready solutions
Hands-on experience with LLMs, AI agent frameworks, RAG architecture, and MCP-based systems.
Expertise in agentic frameworks (LangChain, LangGraph, etc.) and multi-agent system design.
Strong knowledge of cloud-native AI/ML platforms (Azure, AWS, GCP) and MLOps.
Mastery in DevOps, CI/CD pipelines, and AI testing/evaluation frameworks (e.g., Deepeval)
Successful presales background with proposal writing, solutioning, and client engagement.
Exceptional presentation, communication, and executive stakeholder management skills.

Nice-to-Have

Experience with responsible AI, governance, and compliance frameworks.
Exposure to multi-modal AI (text, image, audio, video).
Prior experience working in consulting or client-facing delivery roles.
Contributions to open-source AI frameworks or published research in AI/ML.

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