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Senior specialized LLM/agent role at a well-known pharma in Hyderabad yields moderate applicant competition.
Medium because LLM and agent engineering skills transfer across industries, but life-sciences compliance adds domain specificity.
High due to 9+ years required, 2+ years LLM production experience, specific tech stack, and regulatory/compliance needs.
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Design, build, and deploy autonomous multi-agent AI workflows using orchestration frameworks like LangGraph or similar, involving complex state machines and agent collaboration.
Develop and maintain production-grade, secure, and scalable AI applications integrating LLM platforms (AWS Bedrock, Azure OpenAI, Anthropic Claude, OpenAI GPT-4) with real-time streaming and enterprise APIs.
Ensure compliance with enterprise security, data governance, and Responsible AI standards, while optimizing performance and collaborating with cross-functional teams to drive AI adoption.
Bachelor's or Master's degree in Computer Science, AI/ML, Engineering, Data Science, or related discipline.
9+ years of software engineering experience with 2+ years in production LLM-powered application development.
Proven expertise in agent orchestration frameworks (LangGraph preferred, LangChain, CrewAI, Autogen), async Python (asyncio), FastAPI, cloud LLM platforms (AWS, Azure, OpenAI).
Experience with Docker, Git, CI/CD, cloud platforms (AWS, Azure, or Google Cloud), and enterprise security integration (LDAP, SSO).
Senior engineer proficient in architecting complex multi-agent AI systems beyond chatbot applications, with familiarity in agentic design patterns (ReAct, Plan-and-Execute).
Experienced in LLMOps, prompt engineering at scale, observability tooling (Langfuse, LangSmith), and managing production AI workflows with emphasis on performance and cost optimization.
Able to collaborate effectively with global, cross-functional teams including data engineers and business stakeholders, and mentor junior engineers on async Python and AI deployment best practices.