CareSource is a leading organization in healthcare services, and they are seeking an AI Engineer III – AI Enablement to serve as a technical lead within their AITE team. This role will be responsible for guiding the technical direction and solution design of AI-enabled solutions while collaborating with various teams to ensure successful implementation and governance of AI initiatives.
Responsibilities:
- Lead solution-level architecture for AI initiatives, including data, models, orchestration, security, integration, and observability
- Define and maintain reference architectures, design patterns, and technical standards for AI-enabled solutions
- Translate business problems into actionable designs and clearly communicate tradeoffs, risks, and constraints
- Provide technical decision support and recommendations to AI and IT leadership
- Build proofs of concept and pilots, and implement critical solution components to de-risk delivery
- Develop and validate RAG pipelines, agent-based architectures, and orchestration workflows
- Contribute production-quality code and configurations when hands-on intervention is needed to unblock delivery
- Evaluate emerging AI capabilities, tools, and services through targeted experimentation
- Provide technical guidance to delivery teams, architects, and engineers implementing AI solutions
- Conduct architecture and design reviews to ensure alignment with enterprise architecture, security, and governance standards
- Mentor engineers and architects on AI design patterns, implementation practices, and operational considerations
- Review vendor-proposed designs and implementations for alignment with CareSource standards
- Design, develop, and implement internal automations that support AITE intake, governance workflows, reporting, and operational visibility
- Translate documented process specifications into durable, reusable automation capabilities
- Own the technical design and evolution of AITE’s internal enablement tooling as the team expands
- Architect automation solutions to scale with increased AI demand, additional governance requirements, and broader AITE scope
- Embed governance and Responsible AI requirements into solution architectures from inception
- Partner with Security, Risk, Legal, and AI Governance stakeholders to ensure compliant implementations
- Define solution-level controls for data protection, auditability, and appropriate human oversight
- Provide solution-driven requirements and architectural feedback to AI Platform and Infrastructure teams
- Collaborate on standards for LLMOps, observability, reliability, and cost management without owning platform operations
Requirements:
- Bachelor's degree in Computer Science, Engineering, or a related technical field required; equivalent experience accepted in lieu of degree
- 7+ years of hands-on software or systems engineering experience
- 3+ years designing and implementing AI-enabled or advanced analytics solutions in an enterprise environment
- Demonstrated experience acting as a senior technical lead across multiple teams and stakeholders
- AI solution architecture: strong grasp of modern AI patterns including RAG, agentic workflows, orchestration layers, and evaluation approaches
- Hands-on engineering: strong Python skills and modern software engineering practices (testing, version control, CI/CD as applicable)
- Azure AI ecosystem: experience designing solutions using Azure AI Services (Azure OpenAI, AI Search, Azure Machine Learning, Azure AI Foundry)
- Integration and APIs: ability to design secure, scalable system integrations
- Security-aware design: working knowledge of identity, network isolation, private endpoints, and enterprise security constraints
- Evaluation and observability: ability to define success metrics and interpret performance, cost, latency, and reliability signals
- Automation engineering (AITE-owned): experience designing workflow automation and operational tooling (for example, Power Platform, SharePoint, and service workflow integrations)
- Ability to explain technical concepts and tradeoffs to technical and non-technical audiences
- Strong written documentation skills for architectures, standards, and technical guidance
- Comfort influencing across organizational boundaries without direct authority
- Microsoft Certified: Azure AI Engineer Associate or equivalent
- Azure Solutions Architect Expert (preferred)