Forward Deployed Engineer

About the company

Our client is the AI execution layer for healthcare, life sciences, and wellness. Healthcare has the science, the treatments, and the data; what’s missing is execution. The company turns fragmented health data into precise, measurable action inside the systems enterprises already run.

Together with its partners, the company has supported over 100 million patients and members, generated billions of dollars in measurable value, and helped bring dozens of life-changing drugs to market. Its vision is health abundance in our lifetime, and it believes that won’t come from more data or dashboards, but from execution.

The company is in a phase of explosive growth: it more than doubled its revenue last year, reaching nine-figure ARR, and recently achieved a unicorn valuation. It has been profitable for several years, has a strong cash position, and is backed by top-tier venture investors.

About the role

We’re looking for a Senior Forward Deployed Engineer to own the full technical delivery of AI agent deployments for some of the largest health systems, providers, and pharma organizations in the US. You’ll be an entrepreneurial, client-facing engineer who can architect complex systems, present to C-suite executives, and build production software end-to-end.

You’ll own the full stack end-to-end: making architectural decisions, picking your own tools, and building production AI agents from data ingestion through deployment. There’s no siloed feature work; you’ll shape the system and influence the core product.

Responsibilities

• Own enterprise client engagements end-to-end, from pre-sales demos and requirements gathering through design, integration, implementation, and post-launch support.
• Architect and build production AI agent systems that integrate with complex healthcare systems (EHR/EMR, claims, specialty pharmacy, CRM) under HIPAA.
• Run working sessions and present to executive stakeholders at major health insurance companies and health systems.
• Make independent architectural and design decisions, often as the only engineer in the room: picking tools, scoping integrations, and solving problems on the spot.
• Feed learnings from the field back into the core platform, directly influencing the product roadmap and building reusable components for future deployments.

Requirements

• 5+ years of experience as a software engineer.
• Experience building and owning complex production systems end-to-end (not just demos or prototypes), including the ability to design full system architectures and produce complete architecture diagrams.
• Experience building and deploying customer-facing software systems end-to-end, in production engineering, solutions engineering, solutions architecture, or technical consulting.
• Experience owning full technical delivery for clients, including pre-sales, scoping, and post-sale integration.
• Has put LLM systems or AI agents into production for real users, with evals, guardrails, and monitoring (not just prototypes, demos, or pre-sales builds).
• Healthcare or life sciences domain expertise: patient services, specialty pharmacy, pharmacovigilance, clinical operations, health insurance, or compliance/HIPAA.
• Strong client-facing communication and executive presence, with the ability to run technical sessions for both technical and non-technical stakeholders.
• Fluency in modern languages (Python, JavaScript/TypeScript/Node, Next.js, React), with experience shipping production applications and managing cloud infrastructure (AWS/GCP).
• An entrepreneurial, founder-type mentality
• This is not a 9-to-5 role: you’ll wear many hats, make the call in the room, and be fully accountable for multimillion-dollar engagements.

Nice to have

• Experience as a founding engineer, startup co-founder, startup CTO, or software engineer at a high-growth startup.
• Formal machine learning or internal data science work on healthcare-related projects.
• Experience building data and machine learning pipelines (PySpark, ETL/ELT, unstructured data, document ingestion, predictive models).

Benefits

• $190K–$240K+ total cash compensation (flexible for exceptional candidates).
• Competitive equity, with real liquidity: the company runs secondary offerings every 18–24 months, allowing employees to sell 20% of their vested shares. The last valuation jump was 3x in two years, so you don’t have to wait for an IPO or acquisition to see returns.
• Remote-first, from anywhere in the US (preferred hubs: NYC, Boston, Chicago, and Texas).