Product Engineer, Platform (AI)

Location: New York, NY; hybrid with 3 days per week in the NYC office.

Base pay: $190,000–$200,000 USD annually, plus incentive bonus, stock options, comprehensive benefits, and applicable incentive pay.

Company

hirify.global provides personalized substance use and behavioral health care through clinically driven programs and AI-enabled technology, serving employers, health plans, and more than 750,000 members.

What you will do

• Own and evolve the event-driven data platform, including secure pipelines from product systems, third-party platforms, and external partners into the data warehouse.
• Define Infrastructure as Code and CI/CD practices so environments are reproducible and deployments are safe.
• Build consistent patterns for adding data sources and services, and deliver platform capabilities for analytics, reporting, and member-facing features.
• Own observability, alerting, on-call, and incident response for services and data quality.
• Optimize AWS hosting and data costs while maintaining reliability, and build platform capabilities for agentic workflows.
• Partner with analytics, product, clinical, and commercial teams while improving AI-native development, testing, documentation, and review practices.

Requirements

• Strong production experience as a backend, platform, or systems engineer in a startup or scale-up environment; production cloud infrastructure experience is required.
• Hands-on experience with Terraform, Infrastructure as Code, and building and maintaining CI/CD pipelines.
• Strong AWS experience, including designing, securing, and operating cloud-native services.
• Proficiency in Python and TypeScript with Node across backend services, data pipelines, and tooling.
• Deep experience with event-driven architectures and data platforms, including Kafka or AWS-native streaming and messaging and production integration of third-party data sources.
• Strong observability and reliability practices, including detecting incorrect, late, or incomplete systems and data and creating alerting and runbooks.
• Experience optimizing hosting costs and making architecture trade-offs with spend in mind.
• Familiarity with agentic workflows, strong relational database design and SQL skills, and a product-oriented understanding of downstream platform use.
• Ability to operate autonomously in ambiguous environments, make sound trade-offs with incomplete information, and use AI-augmented engineering workflows while maintaining human judgment and QA discipline.

Nice to have

• Experience with dbt, data modeling, and how analytics teams model and consume data.
• Experience in healthcare, digital health, or safety-sensitive regulated software, including sensitive health data.
• Experience integrating healthcare data sources such as health information exchanges, or marketing and engagement platforms.
• Experience building platforms or foundational systems from 0 to 1 in an early-stage environment.

Culture & Benefits

• Outcome-driven, autonomous engineering culture with accountability for quality, safety, and results.
• Close collaboration with Product, Design, Data, Clinical, and commercial teams.
• AI is used across the software development lifecycle for implementation, testing, and review.
• Work in a regulated, member-impacting domain where reliability, observability, and correctness are first-class concerns.
• Full-time employment includes incentive bonus opportunities, stock options, comprehensive benefits, and applicable incentive pay.
• Visa sponsorship is not available; accommodations can be requested during the interview process.