We are seeking a highly experienced Generative AI professional with strong expertise in Python, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG). The ideal candidate will design, build, and deploy scalable GenAI solutions that accelerate software development and enable intelligent business use cases. This role requires deep hands-on experience with prompt engineering, RAG pipelines, and GenAI MLOps in enterprise environments.

Key Responsibilities

• Apply Generative AI to accelerate software development through code generation, test automation, documentation, and developer productivity tools

• Design and implement business use cases using GenAI such as intelligent assistants, content generation, and enterprise knowledge retrieval systems

• Collaborate with product, engineering, data, and business teams to design, build, and refine scalable GenAI solutions

• Design, optimize, and iterate prompts for tasks including summarization, classification, extraction, and multi-turn conversations

• Apply advanced prompt engineering techniques such as zero-shot, few-shot, chain-of-thought prompting, and guardrails

• Design and implement Retrieval-Augmented Generation (RAG) pipelines to ground LLM responses in enterprise data

• Integrate and manage vector databases such as FAISS, Weaviate, or Pinecone for semantic search and retrieval

• Ensure reliability, accuracy, and safety of LLM outputs through evaluation, monitoring, and governance practices

• Support deployment and lifecycle management of GenAI solutions in production environments

Required Skills and Qualifications

• 10+ years of overall experience with a minimum of 7 years of relevant experience in Generative AI

• Strong programming skills in Python

• Deep understanding of Large Language Models (LLMs) and GenAI architectures

• Proven experience in prompt engineering and prompt optimization techniques

• Hands-on experience designing and deploying RAG-based systems

• Experience working with vector databases such as FAISS, Weaviate, or Pinecone

• Strong problem-solving, analytical, and communication skills

GenAI MLOps & Deployment Experience

• Working knowledge of CI/CD pipelines for AI and LLM-based applications

• Experience with model versioning, monitoring, evaluation, and governance

• Familiarity with MLOps and deployment platforms such as MLflow, Azure ML, AWS SageMaker, or custom deployment frameworks

• Understanding of scalable and secure deployment patterns for enterprise GenAI applications