AI Engineer

At Aperture Cloud, we serve our communities’ most vulnerable seniors through shared intention, pioneering spirit, and the courage to love. These core values and our participant-focus lead the way no matter what. The AI Engineer is accountable for building, testing, and deploying AI-powered solutions that address real-world healthcare challenges within our PACE (Program of All-Inclusive Care for the Elderly) program. This role will leverage enterprise AI models - not build or finetune them - to create intelligent applications such as participant context engines, retrieval-augmented generation (RAG) pipelines, and agentic workflows. The AI Engineer will stay current with the rapidly evolving AI landscape and translate emerging capabilities into production-ready solutions for our business. This role is different because the AI Engineer at Aperture Cloud: Designs and delivers AI-powered solutions that transform how care teams access information, automate complex workflows, and support better participant outcomes through RAG, agentic AI, and enterprise large language models Works at the forefront of applied AI innovation, evaluating emerging technologies and translating them into secure, scalable, production-ready applications that enhance operational efficiency, improve decision-making, and support the evolving needs of the PACE model We care about our team members. That’s why we offer: Medical insurance coverage (Medical, Dental, Vision) Work/life balance - We mean it! 17 days of personal time off (PTO), 12 holidays observed annually, and 6 sick days 401K savings + match Comprehensive compensation package including base pay and bonus And additional benefits! On the day-to-day, you will: Design, build, and deploy AI-powered applications using enterprise LLMs (OpenAI, Anthropic Claude, Google Gemini), as well as translate PACE business requirements, such as building rich participant context, into production-ready AI solutions Architect and implement RAG systems that ground AI responses in Aperture Cloud's proprietary data, ensuring accuracy, relevance, and compliance with healthcare data standards Own the full development lifecycle for new AI use cases from ideation and rapid POC development through validation, iteration, and production deployment Research and build agentic AI workflows (using frameworks such as LangGraph, LangChain, or Copilot Studio) that evolve our systems toward autonomous, goal-oriented agents capable of handling complex multi-step healthcare processes Architect and deploy AI services within private cloud environments (primarily Azure; AWS as needed), utilizing Docker containers, private endpoints, managed identities, and secure VNET configurations Evaluate and integrate across the frontier model landscape, selecting the right model for each use case based on performance, cost, latency, and compliance requirements Implement AIOps and MLOps best practices, monitoring, versioning, automated testing, and CI/CD pipelines, to ensure all AI applications are reliable, scalable, and maintainable Continuously evaluate emerging AI tools, techniques, and model releases, as well as proactively recommend new approaches that can improve participant outcomes, operational efficiency, or developer productivity Job requirements include: Bachelor’s degree required in computer science, AI, computer engineering, or other relevant fields; master’s degree preferred Minimum of three (3) years of hands-on experience in AI/ML engineering, applied AI development, or software engineering with a strong AI focus RAG and Retrieval Systems: Demonstrated experience designing and deploying retrieval-augmented generation pipelines, including vector databases, embedding strategies, chunking optimization, and retrieval evaluation Enterprise LLM Integration: Proven ability to build applications on top of commercial LLM APIs (OpenAI, Anthropic, Google) including prompt engineering, structured output handling, function/tool calling, and context window management Python: Advanced proficiency in Python for AI application development, API integration, and data pipeline construction Cloud & Containerization: Hands-on experience with Azure AI services (AI Foundry, Managed Identities, Key Vault, private networking) and Docker-based deployments in secure cloud environments DevOps & CI/CD: Proficiency with Azure DevOps (or equivalent) for building CI/CD pipelines that automate testing and deployment of AI applications We are seeking an AI Engineer who is curious, innovative, and hands-on, with a passion for applying artificial intelligence to solve real-world healthcare challenges. The ideal candidate combines strong technical expertise with a builder’s mindset and is excited to develop scalable AI solutions that improve the experience of our participants, care teams, and operational partners. If you’re ready to join a team that values both its participants and team members, we’d love to hear from you! Compensation consists of base salary plus bo