• Design and develop AI-driven applications, including single and multi-agent workflows • Build and maintain full-stack solutions (frontend and backend components) • Leverage AI tools and agentic coding practices to accelerate development • Develop orchestration logic for agent-based systems and workflows • Integrate LLM-based capabilities such as document processing, embeddings, and retrieval • Implement best practices for AI evaluations to ensure quality and prevent regressions • Contribute to and maintain CI/CD pipelines and deployment processes • Collaborate with architects and engineering leadership on solution design and standards • Continuously improve development practices and contribute to evolving AI engineering frameworks

• Build the platform foundation, including the MCP Gateway and shared RAG services. • Set technical direction through design documents and ship the components yourself. • Own reliability, observability, and developer ergonomics. • Track the AI tooling ecosystem and feed signal back into the roadmap. • Carry services end-to-end.

• Owning product-level AI solution design and delivery in collaboration with the AI Architect • Building RAG pipelines using EHR data, claims, and clinical text using embeddings and vector search • Developing, fine-tuning, and evaluating LLMs and classical ML models with robust guardrails • Establishing and operating MLOps infrastructure, including experiment tracking, CI/CD, and drift monitoring • Managing reliability, security, and cost for your product’s AI services, including SLOs and incident response • Ensuring HIPAA compliance and responsible AI practices are embedded across development and operations • Reviewing code and experiments with an emphasis on reproducibility - mentoring engineers and data scientists on the team • Contributing reusable AI components back to the shared platform and leveraging GitHub and Microsoft Copilot to improve team productivity

Role Description Our company is looking for a Graduate Instructor, Simulation and Training for Healthcare to support our client remotely. This position will be supporting a government customer, hence only US Citizens may be considered for hire. This opportunity is for one Distance Learning (DL) course taught in the Academic Year (AY) 2026, Quarter 4. The course will start on July 6, 2026 and will only be for one quarter, ending in late September. MV4002: This course focuses on training issues in virtual environments (VEs). VEs have often been considered to be general purpose trainers. However, systems are often built without an understanding of how to build a trainer that can verify that it improves subsequent performance without forming bad habits or other reverse training artifacts. This course will first investigate VE training systems from a theoretical perspective, focusing on learning, memory, and cognition. From this framework, actual training systems will be studied with the focus being on an actual study of training transfer of a real training system. This course is not new to our client and there will be content & materials available from previous iterations of the courses. If you have the required experience and would like to work with a world class graduate institution then please apply! Qualifications - 2+ years’ experience in graduate course level course delivery (within the last 8 years) - A graduate degree in a discipline that supports medical and healthcare modeling and simulation - Broad experience, typically 5 or more years, as an instructor or practitioner in a medical simulation center or similar facility - Evidence of excellent teaching ability - A reputation for expertise in medical and healthcare modeling and simulation, especially within DoD or VA Requirements - Position Type: Part time, Must be U.S. Citizen - Location: Remote or in Monterey, CA - Compensation: $60-$95 per hour, 1099 Benefits - Equal Opportunity Employer - We are committed to a policy of assuring that all applicants for employment are recruited, hired and assigned on the basis of qualifications and merit without discrimination based on any protected classification, including, but not limited to, race, color, religion, sex, sexual orientation, national origin, veteran status, age, disability, handicap, marital status, or any other characteristic protected by applicable laws.