- Company Name
- Foundation Partners
- Job Title
- Founding Product/AI Engineer (HealthTech)
- Job Description
-
**Job Title**
Founding Product/AI Engineer (HealthTech)
**Role Summary**
Architect, build and ship production‑ready clinical AI systems for a virtual care platform. Own the end‑to‑end lifecycle of machine learning models—from inference and safety to monitoring, MLOps, and human‑in‑the‑loop validation—ensuring systems are safe, compliant, and deliver measurable productivity gains for clinicians.
**Expectations**
- Deliver high‑impact features within a high‑stakes, regulated healthcare environment.
- Own outcomes end‑to‑end: design, prototype, deploy, measure, and iterate.
- Balance rapid innovation with rigorous safety, quality, and compliance standards.
- Collaborate directly with clinicians and product teams, turning user needs into technical solutions.
- Shape the technical culture, define standards, and help scale the engineering team.
**Key Responsibilities**
- Design, implement, and maintain LLM inference, retrieval, fine‑tuning, evaluation, and safety pipelines.
- Build and operate clinical‑grade safety infrastructure (hallucination detection, monitoring, governance, incident response).
- Develop reproducible training pipelines, CI/CD for models, audit trails, versioning, and data lineage.
- Conduct human‑in‑the‑loop clinical validation: work with doctors and clinical leads to set acceptance criteria and run prospective studies.
- Deploy models to production (AWS Lambda, API Gateway, DynamoDB, S3) and manage cloud resources.
- Define metrics and monitoring dashboards for model performance and safety.
- Collaborate across front‑end (React / TypeScript), back‑end, and infra teams to integrate AI features into the product.
- Mentor junior engineers and participate in hiring and technical roadmap decisions.
**Required Skills**
- Proven experience shipping production ML/AI systems in high‑stakes or regulated environments.
- Deep knowledge of large language models, model evaluation, safety monitoring, and MLOps.
- Strong judgment on risk, safety, and quality in real‑world deployments.
- Full‑stack engineering capability (AWS serverless, React/TypeScript, Supabase, CI/CD).
- Ability to operate independently, prioritize impact over tickets, and own outcomes.
- Excellent communication skills; able to translate clinical requirements into technical solutions.
**Bonus** –
- Experience in regulated healthcare/medical device development.
- Clinical knowledge or prior delivery of clinician‑facing tools.
- Founding or early‑stage startup experience.
**Required Education & Certifications**
- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related technical field (equivalent professional experience accepted).
- Relevant certifications (e.g., AWS Certified Developer/Architect, ML‑ops certifications) preferred but not mandatory.