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Generative And Agentic AI Engineer

Role Summary

As a senior Generative & Agentic AI Engineer with 10+ years of experience, you will lead the design, development, and deployment of advanced GenAI capabilities and agentic AI workflows. Your role will involve architecting scalable solutions grounded in NLP and Transformer models—including RAG systems and multi-agent orchestration—while ensuring safety, observability, and cost efficiency across enterprise environments. You will mentor teams, define best practices, and drive innovation in AI engineering on cloud platforms (AWS/Azure).

Key Responsibilities

• Lead the architecture and implementation of GenAI services with robust prompt/tool use, function calling, and workflow orchestration; enforce caching, retries, and token/cost controls.
• Design and optimize RAG pipelines (indexing, chunking, embeddings, rerankers) and evaluate retrieval/answer quality; advance to complex agentic patterns (multi-tool, multi-step, multi-agent).
• Apply advanced NLP/Transformer techniques (fine-tuning, adapters/LoRA, distillation) aligned with business and data constraints.
• Engineer production-grade Python services/APIs; integrate vector stores (FAISS, Pinecone), LangChain/LlamaIndex, streaming, and guardrails.
• Ensure operational excellence on AWS/Azure with observability, security, and governance frameworks.
• Mentor junior engineers, establish coding standards, and lead technical reviews to maintain high-quality deliverables.

Must Have Skills

• Deep expertise in GenAI foundations (LLMs, embeddings, prompting).
• Proficiency with Transformer architectures (Hugging Face ecosystem, fine-tuning strategies).
• Advanced NLP applied skills (text processing, evaluation metrics).
• Hands-on experience with RAG and agentic AI design and implementation.
• Strong Python development skills and cloud experience (AWS/Azure).
• API development for model-backed experiences and enterprise integration.

Qualifications And Experience

• B.Tech/M.Tech/MS in Computer Science, Electrical Engineering, or equivalent.
• 10+ years in AI/ML engineering with at least 5 years in GenAI/NLP/Transformer-based solutions.
• Proven track record of leading AI projects and mentoring engineering teams.

EY | Building a better working world 

 
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