GEN AI Sr Lead
- Location INDIA - HYDERABAD - BIRLASOFT OFFICE, IN
- Experience 7-11 yrs
- Job type Full-time
- Posted 7 Oct 2026
You will be taken to Birlasoft’s own careers page to apply. Job ID 60462544.
Job description
Area(s) of responsibility
JD – Senior Developer Gen AI ( 5B Grade) Location- Noida/Pune/Bengaluru/HYD/Mumbai Exp-7-11 Years Notice- Immediate Summary: We are seeking seasoned Senior developer GenAI with overall 10-12 yrs and at least 5-7 years of hands-on experience in developing GenAI/machine learning models and deploying them in a cloud environment, preferably on Google Cloud Platform (GCP). The ideal candidate will design microservice-based solutions, containerize deployments (e.g., GKE), and drive end-to-end SDLC practices. Experience in the pharma domain is a strong advantage. Key Responsibilities Lead end-to-end development of GenAI/ML models: problem framing, data preparation, model selection, training, evaluation, and iteration. Architect and implement microservice-based AI solutions and deploy them in containerized environments (preferably GKE); define APIs and data contracts. Leverage GCP offerings (Vertex AI, BigQuery, Dataflow, Cloud Storage, Pub/Sub, Cloud Run, GKE, etc.) to design scalable AI solutions and efficient data workflows. Knowledge of Retrieval-Augmented Generation (RAG) concepts and processes Proficiency with Google Cloud Platform (GCP) and its AI/ML offerings (e.g., Vertex AI, BigQuery, Dataflow, Cloud Storage, GKE).
Deploy, monitor, and maintain models in production; implement observability (logs, metrics, tracing), cost optimization, and performance tuning. Collaborate with cross-functional teams (data engineers, software engineers, product, regulatory/compliance, analytics) to translate business needs into robust ML solutions. Uphold SDLC standards: requirements gathering, design, development, testing, deployment, maintenance, and documentation; promote reusable patterns and best practices. Mentor and guide junior scientists; contribute to code reviews, standards, and knowledge sharing. Stay current with GenAI advancements and evaluate new tools/approaches; produce reproducible experiments and artifacts.