Senior Applied AI Engineer

Job ID: z5G7h3l6a1kMvyS65NP3c6kZnOPtxH2yKe6fep3Q24o=Job Code: ATS #58676Location: San Diego, CA, United States (Remote)Job Role: Senior Applied AI Engineer Location : San Diego, CAPosition Summary West Health is seeking a Senior Applied AI Engineer to join its Data Science & Analytics team. This is a hands-on, delivery-oriented role for a builder who can rapidly turn ideas into fully working applications and tools that create immediate, measurable value for our organization and the communities we serve. The ideal candidate pairs deep, practical expertise in applied AI with the speed and follow-through to ship. You will partner closely with the Director of Data Science & Analytics to design, build, and deploy intelligent systems—including multi-agent architectures and automated workflows—that amplify the impact of our team and advance our mission of improving healthcare for seniors. Beyond building, you will bring a sharp eye for where AI can add the most value, helping the team spot the highest-impact opportunities and apply the right tool to each one. This role is focused on applied use of existing AI and LLM tools, understanding what each is best suited for and combining them into well-designed, reliable solutions. The right candidate can take a business problem or loosely defined concept and independently develop it into a polished, well-documented tool with a thoughtful user experience. Above all, we are looking for someone genuinely energized by this technology—an engineer who is eager to grow alongside a fast-moving field and is at their best when turning a rough idea into something real and working.General Duties And Responsibilities Applied AI Solution Development: Design, build, and deploy production-quality AI-powered tools and workflows using large language models, AI APIs, and orchestration platforms. Architect and implement multi-agent systems, retrieval-augmented generation (RAG) pipelines, and automated analytical workflows that address real organizational needs and are built for sustained daily use. AI Workflow Orchestration & Integration: Build and maintain intelligent automation pipelines using platforms such as n8n, LangChain/LangGraph, Microsoft Copilot Studio, CrewAI, and similar orchestration tools. Leverage APIs and emerging integration standards such as Model Context Protocol (MCP) to connect AI capabilities with existing data infrastructure (Snowflake, Python, internal systems) and create seamless, reliable workflows that operate with minimal manual intervention. Data Analysis & Strategic Insight: Conduct independent data analysis and contribute analytical thinking to team projects. Proactively identify opportunities where AI can unlock insights, surface patterns in large datasets, and recommend relevant analyses. Translate findings into clear, compelling data stories that inform leadership decisions. Solution Delivery & Follow-Through: Move effectively from concept to deployed solution. Take loosely defined ideas from leadership and independently scope, design, build, and deliver polished tools with intuitive interfaces, proper documentation, and sustainable architecture. Demonstrate consistent follow-through from ideation to completion. Prompt Engineering & LLM Optimization: Develop and refine sophisticated prompt architectures, system instructions, and evaluation frameworks that ensure consistent, high-quality outputs from LLMs. Stay current on model capabilities across providers (OpenAI, Anthropic, Google, open-source models) and recommend the appropriate tool for each use case. Knowledge Management & Documentation: Build and maintain organizational knowledge bases, vector stores, and retrieval systems that enable AI tools to work effectively with proprietary data. Create clear technical documentation so that solutions are maintainable, transferable, and not dependent on any single individual. Collaboration & Communication: Work cross-functionally with data scientists, analysts, visualization developers, and organizational stakeholders. Communicate technical approaches in accessible language and participate in strategic conversations about where AI can drive the greatest organizational impact. Commitment to West Health’s values and mission. This role requires a regular in-office presence from Tuesday through Thursday to support collaboration and business needs during core hours of 9 AM to 5 PM. Mondays and Fridays may be worked remotely, provided availability aligns with standard working hours. The primary focus is on fulfilling responsibilities, delivering results, and collaborating effectively with others.QUALIFICATIONS AND EDUCATION Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field; a Master’s degree is a plus. Minimum 5 years of professional experience in software development, data engineering, or data science, with at least 2 years of hands-on applied AI/LLM experience in a professional setting. Demonstrated experience building and deploying production-ready AI solutions used by real stakeholders. A portfolio or live demonstrations of past work is strongly preferred and will carry significant weight in the evaluation process. Proficiency with AI orchestration and agent frameworks such as LangChain, LangGraph, CrewAI, AutoGen, n8n, or similar tools for building multi-step, multi-agent AI workflows. Working knowledge of retrieval-augmented generation (RAG) patterns, vector databases (e.g., Pinecone, ChromaDB, Weaviate, pgvector), and embedding models. Experience with LLM APIs and platforms including OpenAI, Anthropic Claude, Google Gemini, and/or open-source models via Hugging Face or Ollama. Proficiency in Python and SQL; familiarity with cloud data platforms such as Snowflake is a strong plus. Experience with low-code/no-code AI platforms such as Microsoft Copilot Studio, Power Automate, or similar enterprise AI tooling. Familiarity with emerging AI integration standards such as Model Context Protocol (MCP) and tool-use patterns for connecting LLMs with external systems is a plus. Solid foundation in data analysis, with the ability to independently explore datasets, identify patterns, and communicate findings through clear data narratives. Strong business acumen with the ability to connect technical capabilities to organizational goals and articulate the value behind both the data and the tools. Excellent communication skills with the ability to explain complex AI concepts to non-technical audiences and collaborate effectively across teams. Self-directed, highly motivated, and able to manage projects from ideation through delivery with minimal supervision. Must believe in public health and science-