We are looking for an Engineering Manager to lead and scale the team behind Payer Intelligence - the platforms that automate prior authorization review end to end, from provider intake through AI-driven medical necessity determination. You will own the people, process, and technical direction for a multidisciplinary group spanning backend services, AI/ML engineering, and frontend product work. You are as comfortable in a 1:1 coaching conversation as you are debating an eval strategy or an architecture review, and you thrive when you can connect your team's work to meaningful health outcomes.
Key ResponsibilitiesPeople Leadership & Development- Directly manage a team of engineers across backend, AI/ML, and frontend disciplines
- Drive performance management cycles: goal-setting, mid-year check-ins, year-end reviews, and performance improvement plans when needed
- Partner with recruiting to attract, hire, and onboard top engineering talent, including AI-focused roles where the hiring bar is still being defined industry-wide
- Build and sustain a culture of psychological safety, continuous feedback, and high accountability
- Identify individual growth opportunities and create development plans tailored to each teammate's career goals
Technical Oversight- Provide technical direction and quality standards across Go backend services, Python AI actions, and Vue 3 / TypeScript frontends
- Own the reliability and cost profile of AI/ML pipelines: model selection/upgrades, prompt and context engineering, structured output, document ingestion and OCR, and multimodal handling of clinical PDFs
- Champion a rigorous evaluation practice: golden datasets, regression suites for model and prompt changes, accuracy and drift monitoring, and clear rules for what ships to production
- Participate in architecture and design reviews; ensure decisions balance speed, maintainability, and scalability
- Champion engineering best practices: code review culture, automated testing, CI/CD, Terraform-managed infrastructure, and observability
Delivery & Execution- Own roadmap execution for the Payer engineering, partnering closely with Product, Design, and Clinical teams
- Coordinate work that spans multiple projects, where a single feature often touches a Python action, the Go API, and multiple frontends
- Remove blockers, manage dependencies, and create predictable delivery rhythms via agile practices
- Track and communicate progress, risks, and trade-offs to engineering leadership and cross-functional stakeholders
- Drive continuous improvement in team velocity, quality, and developer experience
Cross-Functional Collaboration- Act as the engineering point-of-contact for Product, Clinical Operations, and payer and provider-facing stakeholders
- Translate clinical and regulatory requirements (medical necessity criteria, CMS program rules) into clear technical scope and feasibility assessments
- Represent AI capabilities and limitations honestly to non-technical audiences, including where a human reviewer stays in the loop
- Partner with the broader engineering leadership team on org-wide standards, tooling, and planning
Required Qualifications- 5+ years of software engineering experience, with at least 2 years in an engineering management or team lead role
- Hands-on depth in at least one of the languages in our stack - Go, Python, or TypeScript - strong enough to read and review code, understand architectural trade-offs, and ask the right questions. Working familiarity with the others, or the appetite to build it quickly
- Practical experience with modern AI technologies: building or leading work on AI-powered products, including prompting, structured output, retrieval, agentic or multi-step pipelines, and evaluation of non-deterministic systems
- Demonstrated experience hiring engineers and conducting full-cycle technical interviews
- Proven track record in performance development: delivering meaningful feedback, managing performance, and growing engineers at multiple levels
- Experience shipping and operating distributed services in production: containers, Kubernetes, CI/CD, and incident response
- Comfort with relational data modeling and SQL
- Strong written and verbal communication skills - you write crisp specs, give direct feedback, and tailor your message to technical and non-technical audiences
Preferred Qualifications- Experience in healthcare, health-tech, or other regulated industries; familiarity with prior authorization workflows is a significant plus
- Familiarity with FHIR, HL7, CRD/DTR/PAS, or other healthcare data standards
- Hands-on experience with Azure (or similar cloud provider) and infrastructure-as-code via Terraform
- Experience with gRPC / protobuf service architectures
- Background in document AI: OCR, PDF parsing, and structured extraction from unstructured clinical documents
- Vue 3 experience; React or Angular is sufficient
- Background contributing to engineering culture initiatives: leveling frameworks, interview training, onboarding programs
Pay TransparencyHumata Health will provide pay transparency information upon application to those in qualifying jurisdictions.
Our salary ranges are based on competitive pay for our company's size and industry. They are one part of the total compensation package that may also include equity, variable compensation, and benefits. Individual pay decisions are ultimately based on several factors, including qualifications, experience level, skillset, geography, and balancing internal equity.
