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AI Architect (AWS Bedrock + Agentic AI + Healthcare) - Fully Remote!!

Palni IncUnited States🇺🇸United StatesPosted 14 Sept 2026

Quick Overview

Seniority
Mid Senior
Work mode
Remote
Location
United States
Posted
2 days ago
SQLAWSDatabricksGenerative AILLMUnity

Job Description

Role: AI Lead / AI Architect

Location: US (Remote) 

Duration: 3+ months (C2H)

Domain: Healthcare / Medicaid / Pharmacy

 Mandatory Skills: AWS Bedrock + Agentic AI + Healthcare. Databricks/Unity Catalog and Medicaid/Pharmacy/PBM

Role Summary

We are looking for a senior AI Lead / Architect to lead the design and implementation of an enterprise Agentic AI solution for a healthcare client. The role requires strong hands-on experience with AWS Bedrock, GenAI/LLM architecture, agent orchestration, enterprise data integration, and customer-facing technical leadership.

Must-Have Skills

  • Strong hands-on experience with AWS Bedrock.
  • Experience designing Generative AI / Agentic AI solutions.
  • Experience with Lang Graph or a similar agent orchestration framework.
  • Strong understanding of LLM agents, tool/function calling, RAG, prompt engineering, and context engineering.
  • Experience integrating AI solutions with APIs and enterprise data platforms.
  • Strong solution architecture and customer-facing technical leadership skills.
  • Healthcare domain experience.
  • Understanding of security, PHI/PII, access control and AI governance.

Strongly Preferred

  • Medicaid, Pharmacy or PBM experience.
  • Experience leveraging Databricks Unity Catalog as the context/metadata plane for AI systems, with Databricks Medallion Architecture as the governed data source for GenAI / Agentic AI solutions.
  • Amazon Bedrock AgentCore.
  • MCP (Model Context Protocol).
  • Natural Language-to-SQL / conversational analytics.
  • Multi-agent / supervisor-agent architecture.

Key Responsibilities

  • Own the end-to-end AI solution architecture.
  • Lead AWS Bedrock and Agentic AI implementation.
  • Design agent workflows and enterprise data integrations.
  • Lead and guide AI Engineers through design and implementation.
  • Work directly with client architecture, engineering, and business teams.
  • Ensure scalability, security, governance, observability, and cost optimization.

 

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