Browse current jobs

Lead GenAI Engineer

Ascendion · Chennai

Apply on employer website

Source and collection record

Read the employer source

Last observed by our collector: . This is not a manual review or a confirmation from the employer.

Employer requisition: 1970324837524014

Job type and experience labels are automated discovery categories. The employer determines eligibility. Original experience wording was not retained separately; check the current employer page.

How sourcing and classification work · Report a discrepancy

Your application evidence checklist

Mark the statements you can support after reading the employer source. This checklist stays on this page; it does not score your eligibility or submit an application.

0 of 3 checks marked. Keep unresolved requirements as questions for the employer.

Collected role description

Role Overview We are hiring a Lead GenAI Engineer with 7–10 years of experience to drive the design, architecture, and delivery of enterprise-scale GenAI platforms. This role requires strong technical leadership and proven experience in building production-grade AI systems end-to-end . Key Responsibilities Define architecture and technical strategy for GenAI platforms and solutions Lead design and implementation of complex RAG systems and agentic workflows Drive adoption of LangChain / LangGraph and advanced LLM orchestration frameworks Architect high-performance vector search and retrieval systems Oversee deployment strategies, including scalable cloud-native architectures Ensure reliability, observability, and governance of AI systems in production Lead and mentor engineering teams; conduct design reviews and code reviews Collaborate with stakeholders to align AI solutions with business goals Evaluate and integrate new tools, models, and frameworks in the GenAI ecosystem Required Skills Expert-level proficiency in Python Extensive experience with RAG, LLMs, and prompt engineering at scale Strong expertise in LangChain / LangGraph and agent-based architectures Deep experience with Vector Databases and retrieval optimization Proven track record of deploying production-grade GenAI applications Strong experience with cloud (AWS/GCP/Azure), Kubernetes, and microservices architecture Solid understanding of system design, scalability, and distributed systems Preferred Qualifications Experience leading GenAI/AI transformation initiatives Strong knowledge of LLMOps, MLOps, and governance frameworks Exposure to fine-tuning, evaluation frameworks, and guardrails Prior experience in client-facing or consulting roles Common Must-Have Across All Roles Must have worked on at least one productionized AI/GenAI application Should have been involved in the end-to-end lifecycle : Problem definition → Data → Model → RAG → Deployment → Monitoring Strong ownership mindset and ability to work in fast-paced environments

Collected minimum qualification

Experience leading GenAI/AI transformation initiatives

Collected experience requirement

7-10 years