AI Engineer

Description
Remote
Our client seeks an AI Engineer to build, test, and deploy AI-powered solutions that address healthcare challenges within the PACE program. The role focuses on leveraging enterprise AI models to deliver applications such as participant context engines, RAG pipelines, and agentic workflows. The AI Engineer will translate emerging AI capabilities into production-ready solutions, collaborate with stakeholders, and support team culture and mission.
This is a full-time, permanent opportunity, offering a competitive salary and comprehensive benefits package. Qualified applicants must be willing and able to work on a w2 basis.
Salary: $125,000 - $165,000/ yr. w2
Responsibilities
Design, build, and deploy AI-powered applications using enterprise LLMs to meet PACE business requirements.
Architect and implement RAG systems grounded in proprietary data with accuracy, relevance, and compliance.
Own the development lifecycle from ideation and POC through validation, iteration, and production deployment.
Research and build agentic AI workflows using frameworks such as LangGraph, LangChain, or Copilot Studio.
Architect and deploy AI services in private cloud environments, primarily Azure, using secure configurations.
Evaluate and integrate across multiple models based on performance, cost, latency, and compliance.
Implement AIOps and MLOps practices including monitoring, versioning, automated testing, and CI/CD.
Continuously evaluate emerging AI tools and models and recommend improvements.
Work a varied schedule that may include evenings, nights, weekends, and overtime.
Complete required documentation accurately and on time while protecting privacy and confidentiality.
Follow policies and procedures, participate in quality improvement, training, and meetings.
Communicate regularly with the supervisor and team on workload and priorities.
Complete mandated trainings and occupational health screenings on time.
Exercise flexibility as business needs evolve and perform other duties as assigned.
Experience Requirements
Minimum three years of hands-on experience in AI/ML engineering, applied AI development, or software engineering with an AI focus.
Demonstrated experience designing and deploying RAG pipelines including vector databases and retrieval optimization.
Experience building on commercial LLM APIs with prompt engineering, structured outputs, tool calling, and context management.
Advanced proficiency in Python for AI applications, APIs, and data pipelines.
Hands-on experience with Azure AI services and Docker in secure cloud environments.
Proficiency with DevOps and CI/CD using Azure DevOps or equivalent.
Understanding of agentic architectures and frameworks such as LangChain, LangGraph, Semantic Kernel, or Copilot Studio.
Experience in Agile or Scrum with iterative development and rapid POCs.
Familiarity with HIPAA, PHI handling, and healthcare compliance preferred.
PACE program knowledge preferred.
Experience benchmarking LLM providers across accuracy, cost, latency, and safety preferred.
Secondary experience with AWS AI/ML services is a plus.
Strong organizational and communication skills with ability to work independently and prioritize.
Experience working with people from diverse backgrounds and a commitment to serving vulnerable seniors.
Education Requirements
Bachelors Degree in Computer Science, AI, Computer Engineering, or a related field required. Masters Degree preferred.

Work arrangement
Yes