← Back to Jobs
Lead Data Scientist-Agentic AI Engineer-Bangalore Location-Immediate
Genpact
AI/ML & DataBengaluru
5 days ago
💻 Open Source✨ NewHeavy focus on agentic AI and LLM-based platforms—building AI dev tools, multi-agent systems, and RAG/vector search workflows.
About the Role
Lead-level AI engineer to design and deliver enterprise-scale Agentic and Generative AI platforms using LLMs, multi-agent orchestration, RAG/GraphRAG and vector search. Own end-to-end architecture, MLOps/LLMOps, cloud-native deployments, mentor AI teams, and engage with senior stakeholders to translate business needs into scalable AI solutions.
Job Description
Role
Lead architecture, design, and delivery of enterprise-scale Agentic AI and Generative AI solutions. Serve as the senior technical authority for AI initiatives, owning solution and reference architectures, setting engineering standards, and guiding multi-year AI roadmaps.
Key Responsibilities
- Architect and lead design of enterprise-grade Agentic AI, Generative AI platforms, and AI-powered copilots.
- Define reference architectures for autonomous multi-agent systems, retrieval-augmented generation (RAG/GraphRAG), embeddings, vector databases, and semantic search.
- Own end-to-end architecture for RAG/GraphRAG solutions and enterprise knowledge integration.
- Design and develop scalable, secure, highly available AI services and APIs using Python and cloud-native patterns.
- Establish and govern MLOps and LLMOps frameworks, including model lifecycle management, observability, monitoring, and Responsible AI practices.
- Set organizational standards for prompt engineering, model evaluation, fine-tuning, and optimization of LLM-based applications.
- Lead architecture review boards, technical governance, and mentor senior AI Engineers and Architects.
- Engage with CxO-level stakeholders and clients to shape AI strategy and translate business vision into technical solutions.
- Drive PoCs, enterprise accelerators, and early adoption of emerging AI technologies.
Requirements
- Significant experience in Agentic AI, Generative AI, Data Science, and enterprise software engineering with production deployments and technical leadership.
- Expert-level programming skills in Python and SQL; strong enterprise API design and development experience.
- Deep expertise in Deep Learning, NLP, prompt engineering, RAG/GraphRAG, embeddings, vector databases, and semantic search.
- Hands-on experience with Agentic AI frameworks (e.g., LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen) and multi-agent orchestration.
- Experience integrating and optimizing foundation models (OpenAI, Azure OpenAI, Gemini, Claude, AWS Bedrock) in enterprise architectures.
- Architectural experience with cloud platforms (AWS, Azure, GCP), containerization (Docker, Kubernetes), and enterprise CI/CD pipelines.
- Demonstrated ownership of MLOps/LLMOps, Responsible AI, AI governance, model monitoring, observability, and evaluation frameworks.
- Strong analytical, communication, stakeholder management, mentoring, and leadership skills.
Good to Have
- Experience with Model Context Protocol (MCP), Knowledge Graphs, multimodal AI, Databricks, Snowflake, Spark/PySpark.
- Prior Principal Engineer / AI Architect experience, published thought leadership, patents, conference talks, or relevant cloud/ML certifications.
Education
- Bachelor’s or Master’s degree preferred in Computer Science, AI, Data Science, Engineering, Mathematics, Statistics, or related field.