Senior Engineering Manager (AI Platform)

Location: United States — Remote

Company

hirify.global builds telehealth infrastructure and support solutions that enable virtual care delivery across all 50 states.

What you will do

• Build, hire, onboard, and develop Applied AI Engineering teams across Senior, Staff, and Senior Staff levels.
• Own the roadmap, delivery, launch, and ongoing operation of production LLM-based agents and assistants.
• Set technical direction for agent runtime and orchestration, retrieval, model access, observability, and architecture trade-offs.
• Establish evaluation sets, regression tests, and AI-graded evaluations as part of the software delivery process.
• Own reliability, on-call, incident response, provider fallbacks, model upgrades, and AI spend across production systems.
• Partner with Product, Operations, clinical, executive, Security, and Compliance stakeholders on prioritization, safety, privacy, and HIPAA requirements.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related technical field.
• 10+ years of software engineering experience, including 3+ years managing engineers directly through hiring, performance management, and career development.
• Production experience leading or building LLM-based systems used by real users, beyond demos, prototypes, or personal projects.
• Experience managing Senior and Staff-level engineers and earning their technical trust.
• Technical understanding of agent runtime, evaluation, retrieval, and observability sufficient to review designs and make architecture decisions.
• Experience measuring AI system performance with evaluation data and applying evaluation rigor.
• Strong production engineering fundamentals across testing, services, APIs, deployment, incident management, and on-call.
• Experience leading teams that handle sensitive data with a security-first mindset.
• Comfort working in a greenfield space and communicating clearly with technical and non-technical partners.

Nice to have

• Healthcare, finance, or insurance experience, including PHI or HIPAA exposure.
• Experience leading production services on Google Cloud.
• Experience scaling an engineering team from zero or from one team into several teams.
• Experience migrating between model versions or providers.
• Machine learning experience beyond LLMs.
• Experience leading an internal platform used by other engineering teams.

Culture & Benefits

• Full-time role in a relatively flat organization with autonomy, competence, and belonging as core values.
• Medical, dental, and vision plans.
• Flexible Spending Accounts and Health Savings Accounts.
• Flexible PTO.
• 401(k) with company match, life insurance, pet insurance, and additional benefits.