Back
Niche LLM and regulated-pharma requirements reduce applicant pool despite metro Hyderabad location.
Regulatory, pharmacovigilance, and GxP requirements create strong preference for healthcare-experienced candidates.
Strict years, LLM, GxP, and specific tech mandates make shortlisting highly selective.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead the design and implementation of a multi-agent AI platform for adverse event data processing in pharmacovigilance, ensuring regulatory compliance and safety.
Own architecture and integration of AI agents using AWS Bedrock, Anthropic Claude, LangGraph, and related frameworks, including prompt engineering and evaluation pipelines.
Define and implement GxP-compliant validation strategies (IQ/OQ/PQ) and contribute to technical documentation and CI/CD/MLOps for LLM-based systems.
7+ years of hands-on ML/AI production experience, with 2+ years specifically on large language models at application level.
Proficient with Anthropic Claude APIs, AWS Bedrock (model invocation, knowledge bases), Lambda, S3, IAM, CloudTrail.
Experience building multi-agent LLM orchestration systems using tools like LangGraph, LangChain, CrewAI, or Strands SDK.
Bachelor's degree in computer science or related field, or equivalent experience.
Experienced in regulated environments emphasizing compliance, quality, and patient safety, especially in pharma or healthcare sectors.
Strong technical skills in AI system architecture, prompt engineering, and secure enterprise integrations, with ability to communicate complex concepts to regulatory and quality teams.
Proven ability to own end-to-end AI system validation and deployment in a growth-focused, fast-paced setting involving cross-functional collaboration.