Solutions Engineer
Key Responsibilities
Pre-Sales & Field Engineering Partner with Sales and Customer teams to scope and design high-impact AI agent workflows tailored to payer and provider use cases (e.g. prior auth, clinical documentation, HEDIS gaps). Develop and deliver technical demos, prototypes, and live solutions using the AI Studio. Write clean, modular code to orchestrate multi-agent AI workflows that replicate common healthcare data patterns and edge cases. Build trust with technical and non-technical stakeholders — translating business goals into actionable AI-powered solutions. Provide hands-on technical support during pilots, proof-of-concepts, and go-lives. Platform & Product Feedback Loop Be a power user and builder on the AI platform — stretch its limits, then help us improve it. Identify patterns across customers and feed insights back to Product, Engineering, and GTM teams. Build reusable agent templates and playbooks for core healthcare workflows. Must-Have Qualifications 5+ years of experience in Solutions Engineering, Field Engineering, or Pre-Sales in healthcare tech, ideally with exposure to AI/ML platforms. Deep knowledge of U.S. healthcare workflows — especially payer/provider intersections. Strong programming ability (Python or JavaScript preferred) — you can build and demo, not just whiteboard. Experience working with or designing multi-agent systems or LLM-based applications. Ability to communicate clearly and confidently with engineers, clinicians, and executives. Full-stack ownership mindset — you see the job through, not just the slide deck. Thrives in high-velocity, ambiguous, startup environments — you build fast and course-correct faster. Bonus Points Experience with AI Studio or similar platforms (Lang Chain, ReAct, Semantic Kernel, etc.). Background in building scalable agentic workflows, RAG pipelines, or healthcare-specific AI tools. Open-source contributions or technical blogs related to AI agents, clinical workflow