Specialist, AI Engineering – GenAI & Agentic AI Lead

About the role

Join MSD’s Technology Center in Hyderabad as a Senior AI Engineer driving end‑to‑end development of Generative AI (GenAI) applications. You will lead the design of agentic AI systems, prompt engineering, and Retrieval‑Augmented Generation (RAG) pipelines while ensuring performance, scalability, and responsible AI practices.

Key responsibilities

• Implement agentic AI solutions using frameworks such as LangChain, Google ADK, Strands, and Semantic Kernel.
• Apply advanced prompt engineering techniques (ReAct, few‑shot, chain‑of‑thought, prompt chaining) to improve LLM accuracy and robustness.
• Build multimodal AI applications that combine text, images, and structured data for enterprise use cases.
• Develop reusable agent tooling, including Model Context Protocol (MCP) and Agent‑to‑Agent (A2A) communication patterns.
• Collaborate with cross‑functional stakeholders to translate business problems into scalable GenAI solutions.
• Support deployment and operationalization on cloud platforms (AWS, GCP) and leverage tools like Claude CLI, GitHub Copilot, Vertex AI, and Codex.

Required profile

• Master’s degree in a quantitative field (e.g., Computer Science, Statistics, Engineering).
• Minimum 5 years of experience in the full ML lifecycle, including production deployment on cloud infrastructure (Databricks preferred).
• Proven technical leadership and mentorship abilities.

Required skills

• Python programming.
• LangChain, Google ADK, Strands, Semantic Kernel.
• Prompt engineering (ReAct, few‑shot, chain‑of‑thought).
• RAG architectures, embedding generation, retrieval optimization.
• AgentOps practices (observability, tracing, logging).
• Model Context Protocol (MCP) and Agent‑to‑Agent (A2A) patterns.
• LLM ecosystems, Claude CLI, GitHub Copilot, Vertex AI, Codex.
• Cloud platforms: AWS, GCP.
• Databricks, TensorFlow, PyTorch.
• NLP, tokenization, embeddings, transformer models.