GenAI Tech Lead – RAG, Agentic Workflows & LLMOps

Tata Consultancy Services; Paris; On-site; EUR 90,000 - 150,000; Full time

Benefits offered by this job

Holiday Bonus

Profit sharing

CSE

Job summary

Tata Consultancy Services in Paris is hiring an AI Tech Lead to design and productionize Generative AI solutions with a strong focus on RAG, fine-tuning, and orchestration in a cloud environment.

You will build end-to-end GenAI applications, optimize pipelines, implement agentic workflows, and productionize with MLOps practices, working across AWS/Azure/GCP and enterprise security standards.

Qualifications

• Experience in AI/software engineering with strong Python
• Hands-on experience delivering GenAI/RAG solutions in production
• Experience with one cloud provider: AWS, Azure, or GCP
• Familiarity with vector databases/search and retrieval strategies
• Solid engineering practices: Git, testing, Docker
• PyTorch/deep learning background, strong data science foundations
• Experience with RAG/agent evaluation and prompt & data security
• Knowledge of enterprise security/compliance (IAM, encryption, auditing)

Responsibilities

• Build end-to-end GenAI applications (APIs/services, enterprise integration)
• Design and optimize RAG pipelines (ingestion, chunking, embeddings, vector indexing, retrieval, reranking)
• Implement agentic workflows and orchestration (LangChain/LlamaIndex)
• Apply fine-tuning/adaptation (PEFT/LoRA) and evaluation strategies
• Productionize with MLOps: CI/CD, observability, monitoring, cost, governance

Skills

Python

GenAI engineering

Cloud platforms

RAG pipelines

LLMOps

MLOps

vector databases

Keras/PyTorch

Security & governance

Tools

Docker

Kubernetes

Git

LangChain

LlamaIndex

Job description

Tata Consultancy Services in Paris is hiring an AI Tech Lead to design and productionize Generative AI solutions with a strong focus on RAG, fine-tuning, and orchestration in a cloud environment.

You will build end-to-end GenAI applications, optimize pipelines, implement agentic workflows, and productionize with MLOps practices, working across AWS/Azure/GCP and enterprise security standards.