About the Role

ENGIE’s S&EM is building a next-generation platform that deploys large-language-model agents across every business line - energy markets, asset operations, energy supply B2B and B2C.

We are looking for a highly experienced Senior Agentic / Gen AI Engineer to join our AI Center of Excellence and lead our business line AI team in India. In this strategic role, you will lead the design, development, and industrialization of Large Language Model (LLM) and Generative AI solutions at enterprise scale. You will work at the intersection of cutting-edge AI research and robust production engineering, shaping the future of how our organization leverages AI and agentic.

Key Responsibilities

• Architect and build end-to-end GenAI applications, including RAG pipelines, LLM fine-tuning, prompt engineering frameworks, and agent-based systems
• Design and maintain scalable MLOps infrastructure: model versioning, CI/CD for ML, monitoring, and automated retraining pipelines
• Build end-to-end workflows: triggers in n8n → Ray Serve endpoints → vector memory (pgvector, Azure AI Search) → adaptive cards in Teams. Might also use copilot studio for simple cases.
• Collaborate with product, data, and business teams to translate complex requirements into production-ready AI solutions

• Own cloud infrastructure with AKS, Terraform/Bicep, and GitHub Actions; secure everything with Entra ID, Key Vault and Managed Identity.

• Instrument, monitor and optimise cost/latency using OpenTelemetry, Grafana and LangSmith
• Evaluate and integrate emerging AI tools, frameworks, and foundation models (OpenAI, Anthropic, etc.)
• Ensure reliability, security, and compliance of AI systems in regulated enterprise environments
• Mentor junior engineers and contribute to building an internal AI engineering culture

Required Qualifications

• 7+ years of experience in software or ML engineering, with at least 3 years focused on LLM / GenAI systems
• Strong hands-on expertise with frameworks such as LangChain, LlamaIndex, Hugging Face, or similar
• Solid experience with MLOps tooling: MLflow, Kubeflow, Weights & Biases, or equivalent
• Proficiency in Python and cloud platforms (AWS, Azure, or GCP), including containerization (Docker, Kubernetes)
• Experience with vector databases (Pinecone, Weaviate, pgvector, etc.) and retrieval-augmented generation (RAG)
• Deep understanding of model evaluation, observability, and responsible AI principles
• Excellent communication skills — able to present technical topics to non-technical stakeholders

Nice to Have

• Experience in a large enterprise or regulated industry (finance, healthcare, manufacturing, etc.)
• Familiarity with LLM security topics: prompt injection, data leakage, guardrails
• Contributions to open-source AI projects or published research
• Knowledge of EU AI Act or other AI compliance frameworks