Assistant Vice President - AI Engineer (Generative AI and LLM Platform Enablement)

AI Engineer (Generative AI / LLM Platform & Enablement)​, AVP

: Job Title: AI Engineer (Generative AI / LLM Platform & Enablement)​, AVP Location: Bangalore, India Role Description As an AI Engineer in the AI Enablement Team, you will design and deliver enterprise‑grade capabilities that enable teams to adopt Generative AI safely and effectively. You will operate across platform engineering and applied GenAI development, while acting as a trusted advisor to engineers and business users—translating emerging AI capabilities into practical, scalable solutions that drive real business impact. What we’ll offer you As part of our flexible scheme, here are just some of the

that you’ll enjoy Best in class leave policy Gender neutral parental leaves 100% reimbursement under childcare assistance benefit (gender neutral) Sponsorship for Industry relevant certifications and

Employee Assistance Program for you and your family members Comprehensive Hospitalization Insurance for you and your dependents Accident and Term life Insurance Complementary Health screening for 35 yrs. and above Your

Build and Evolve the GenAI Platform Develop reusable platform components for LLM access, orchestration, and agent-based workflows. Design and implement RAG and CAG patterns , including ingestion pipelines, retrieval strategies, and context assembly to ensure high-quality grounded outputs. Establish reusable prompting frameworks , templates, and standards to enable consistent and scalable use of GenAI across the organization. Apply GenAI Fundamentals in Practice Demonstrate strong understanding of Generative AI core concepts , including: Prompt engineering (structured prompting, system prompts, optimization) Retrieval-Augmented Generation ( RAG ) and Context-Augmented Generation ( CAG ) Programmatic prompting approaches (e.g., DSPy ) Translate these concepts into robust, production-ready implementations, and reusable patterns for others. Work Across End-User and Developer Ecosystems Leverage and integrate both: End-user oriented tools such as Microsoft Copilot, Copilot Studio, and AI Builder Developer-oriented frameworks and platforms such as Python, LangChain, Vertex AI, and Snowflake Cortex AI Optionally contribute to broader engineering stacks (e.g., Java, Spring AI, React) where needed. Actively use and promote coding copilots (e.g., GitHub Copilot, Gemini Code Assist, Claude Code) to accelerate development and improve engineering productivity. Enablement and Consulting Mindset Act as a consultant within the organization , helping teams maximize the value of existing tools and platforms rather than defaulting to bespoke builds. Support engineers and business users in understanding how and where GenAI delivers value and guide them towards pragmatic solution patterns. Create reusable assets such as reference architectures, starter kits, and best practices. Communicate complex technical concepts in a clear, actionable way for both technical and non-technical audiences. Quality, Governance, and Operational Excellence Implement evaluation, observability, and quality frameworks for LLM applications. Ensure solutions meet enterprise standards for reliability, security, and responsible AI adoption. Align with governance, risk, and compliance