Mid/Senior Forward Deployment Engineer
Confirmed on the employer's own hiring board on Oct 10, 2026. First seen by Alion on Jun 20, 2026. Hippocratic AI scores B on the Alion truth index.
Join our team as a Mid/Senior Forward Deployment Engineer, where you'll work closely with Deployment Strategists, engineers, and clinical experts. You'll have high technical ownership and autonomy in the field, with direct access to our product, ML research, and engineering leadership. Your responsibilities will include designing and implementing RAG pipelines, building tool-calling and Model Context Protocol architectures, developing production Python code, executing end-to-end deployments, monitoring and owning production systems, and partnering with customers as a technical expert. The ideal candidate will have deep expertise in LLM techniques, 3+ years of professional software engineering experience, and healthcare IT experience.
Missions
- Design and implement RAG pipelines that ground conversational AI responses in customer clinical data, ensuring accuracy, safety, and relevance to healthcare workflows.
- Build tool-calling and Model Context Protocol (MCP) architectures that enable AI agents to interact securely with customer systems-EHRs, data warehouses, and operational tools.
- Execute end-to-end deployments including infrastructure setup, integration testing, production monitoring configuration, cutover planning, and go-live execution.
Profil recherché
- Deep expertise in LLM techniques including retrieval-augmented generation (RAG), prompt engineering, tool calling, LLM-as-judge, and related advanced patterns- 3+ years of professional software engineering experience with strong Python fundamentals and production software development experience
- Demonstrated experience building integrations with APIs, databases, or enterprise systems; comfort with async patterns, error handling, and reliability engineering
- Bachelor's degree in Computer Science, Software Engineering, or a related technical field
- Hands-on experience with LLM frameworks (LangChain, LangSmith, or similar) and deep understanding of modern LLM development patterns and best practices
- Experience with Model Context Protocol (MCP) or similar frameworks for tool integration and multi-system orchestration
- Production DevOps or infrastructure experience, including setting up monitoring, alerting, logging, and incident response systems
- Healthcare IT experience, including EHR integrations (Epic, Cerner, Athena), FHIR, HL7, or healthcare data standards
- Track record deploying AI systems or working with LLMs in production environments, managing latency, reliability, and operational complexity
- Experience in mission-critical or safety-sensitive systems where reliability and error handling are non-negotiable
- Startup or high-growth technology background, particularly in technical leadership or ownership roles