Description

Architect and deliver agentic AI systems, LLM-powered applications, and end-to-end ML/GenAI architectures.

This role is on-site.

Responsibilities

• Design and implement agentic AI systems using LLMs, autonomous agents, and multi-agent orchestration frameworks.
• Architect end-to-end ML and GenAI solutions including data pipelines, vector databases, RAG patterns, and governance frameworks.
• Build, fine-tune, and optimize ML/Deep Learning/NLP models using Python and mainstream frameworks.
• Architect scalable CI/CD pipelines for AI/ML solutions and deploy systems using Docker/Kubernetes.
• Conduct architectural reviews, guide data scientists and engineers, and define solution patterns and best practices.

Required Skills

• 10+ years of overall experience, including 8+ years in AI/ML Architecture and 3+ years in Agentic AI/LLM systems.
• Strong proficiency in Python and TensorFlow.
• Hands-on experience with LLMs, RAG, LangGraph, LangSmith, LlamaIndex, Semantic Kernel, and AutoGen.
• Experience designing and deploying AI agents on enterprise-grade runtimes (e.g., Amazon Bedrock AgentCore).
• Proficiency in CI/CD pipelines, Docker, and Kubernetes for scalable deployment.
• Knowledge of agent runtime capabilities: state management, memory handling, asynchronous execution, and API integration.
• Experience with AI governance, safety, hallucination detection, and human-in-the-loop evaluation.

Preferred Skills

• Experience in the Pharmacy or Healthcare domain, including familiarity with FHIR, HL7, NCPDP, and EHR/EMR systems.
• Exposure to healthcare compliance standards such as HIPAA, GxP, and FDA regulatory frameworks.

Key Skills

Education

Any Graduate