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responses and apply retrieval-augmented generation (RAG) techniques hands-on.\n\n- Learn and apply best practices for monitoring AI applications, running automated tests, and using CI/CD pipelines to keep systems reliable and up to date.\n\n- End to end accountability of requirements confirmation, POC and demo, solutioning, development and testing, change control and deployment, support and documentation, and research and innovation.\n\n- Excellent written and verbal communication skills with a commitment to prompt, clear responses.\n\n- Comfortable collaborating asynchronously with distributed onshore and offshore peers.\n\nTechnical Requirements :\n\nMust have :\n\n- Familiarity with agentic development patterns such as Agent-to-Agent (A2A) communication, self-attestation, and multi-step autonomous workflows (especially with Copilot, Copilot Studio, and AI Foundry).\n\n- 3+ years of experience in General AI/ML development and software engineering with a strong AI focus.\n\n- 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Healthcare domain: Familiarity with HIPAA, PHI handling, and the compliance requirements unique to healthcare technology.\n\n- PACE program knowledge: Understanding of the PACE model of care and how technology can improve participant outcomes and operational workflows.\n\n- Confluence: Familiarity with Confluence for documentation and knowledge management.\n\n- Agile / Scrum: Experience with Agile ceremonies including sprint planning, stand-ups, retrospectives, and backlog grooming.\n\n- MS licensing models: Familiarity with MS copilot licensing, tokens, and pricing.\nSkills\nPython, RAG, Cloud, Confluence, Eagle PACE, Agile, Scrum, C#, ASP, MVC, 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