Agentic AI Engineer

What You''ll Do

• Design, develop, and deploy enterprise-grade AI applications using modern software engineering best practices.
• Build and enhance agentic AI solutions, AI copilots, and intelligent workflow automation.
• Develop LLM-powered applications leveraging Retrieval-Augmented Generation (RAG), tool calling, and orchestration frameworks.
• Build scalable APIs, microservices, and integrations supporting enterprise AI platforms.
• Collaborate with data scientists to productionize machine learning and AI solutions.
• Implement testing, monitoring, observability, and governance practices for AI applications.
• Ensure AI solutions meet security, compliance, and responsible AI standards.
• Contribute to architecture decisions for enterprise AI platforms and reusable application frameworks.
• Work within Azure and Microsoft''s AI ecosystem while supporting multi-cloud best practices where appropriate.
• Participate in code reviews and promote engineering excellence across the team.

Current AI Initiatives

• This role will contribute to several strategic AI initiatives, including:
• Payer Intelligence Platform
• Monitor payer policy changes using AI.
• Assess operational impact of policy updates.
• Support managed care teams in prioritizing actions and dispute resolution.
• Clinical Chart Review: Build agentic AI solutions using EHR and clinical documentation.
• Support patient cohort identification.
• Generate clinical insights for quality improvement initiatives.
• Population Market Intelligence: Analyze internal and external datasets.
• Generate recommendations for service line growth.
• Identify emerging healthcare market opportunities.

Required Qualifications

• MUST HAVE A Bachelor''s degree in Computer Science, Engineering, Data Science, or a related technical field. Master''s degree preferred. Equivalent professional experience may be considered in lieu of an advanced degree.
• Approximately 3+ years of experience in AI engineering, machine learning engineering, data engineering, software engineering, or a related technical discipline.
• At least 2 years of experience designing, building, and supporting production-grade enterprise applications.
• Hands-on experience developing applications using Large Language Models (LLMs).
• Experience implementing Retrieval-Augmented Generation (RAG) architectures.
• Experience building agentic AI applications, AI assistants, or workflow automation solutions.
• Strong Python programming skills.
• Experience building and consuming RESTful APIs.
• Knowledge of software engineering best practices, including testing, version control, CI/CD, and maintainable application design.
• Experience designing scalable enterprise application architectures.

Preferred Qualifications

• Experience within healthcare, provider organizations, payer organizations, or biomedical environments.
• Experience with Microsoft Azure and Azure AI services.
• Familiarity with GitHub Copilot and the Microsoft AI ecosystem.
• Experience with AI governance, responsible AI practices, observability, guardrails, and model monitoring.
• Background in MLOps and production AI deployment.
• Technical Environment
• Python
• Azure (preferred)
• GitHub Copilot
• Microsoft AI ecosystem
• REST APIs
• Microservices
• Enterprise AI architecture
• Tool-calling frameworks
• Retrieval-Augmented Generation (RAG)