Senior Technical Lead - AI Product Engineering (CMH Health)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Technical Lead - AI Product Engineering (CMH Health) based in the United States.

As a Senior Technical Lead, you will shape the technical direction and delivery of AI-enabled healthcare products, transforming complex actuarial and business workflows into reliable, scalable software. You will take ownership of key products and engineering workstreams, guiding architecture, implementation, quality, and production performance. Combining hands-on development with technical leadership, you will make critical engineering decisions while mentoring others to take greater ownership. You will work closely with product owners, consultants, domain experts, and end users to ensure solutions address real business needs. AI-assisted engineering will be central to your approach, helping teams accelerate development while maintaining rigorous standards for accuracy, security, and reliability. This role offers the opportunity to influence the evolution of commercial healthcare technology products in a collaborative, forward-deployed engineering environment.

Accountabilities

You will be accountable for the technical outcomes of your assigned products and workstreams, balancing hands-on engineering with architectural leadership, delivery ownership, and team development.

• Define pragmatic architectures, including service boundaries, APIs, data models, and system integrations, balancing reliability, security, performance, cost, and maintainability.

• Explain technical trade-offs and select straightforward, effective solutions that meet business and product requirements.

• Translate business needs into actionable technical plans by collaborating with product owners and domain experts, clarifying requirements, identifying dependencies, and breaking work into small, testable increments.

• Own technical delivery commitments and proactively communicate risks related to scope, budget, dependencies, and timelines.

• Build verification into the development lifecycle by strengthening automated testing, data-quality controls, regression checks, and AI evaluation practices.

• Ensure releases are supported by clear evidence that complete workflows function correctly, rather than relying solely on individual component testing.

• Improve production readiness through effective deployment, monitoring, rollback, and support practices.

• Investigate recurring production issues and implement targeted improvements that reduce failures and manual intervention.

• Guide the responsible use of AI-assisted development tools and coding agents, including context management, generated-code reviews, evaluation, and appropriate human oversight.

• Measure the impact of AI-assisted engineering through improvements in end-to-end delivery outcomes rather than code volume alone.

• Develop reusable engineering patterns, shared capabilities, and tooling where they address demonstrated needs, encouraging adoption without unnecessary complexity or approval bottlenecks.

• Delegate meaningful technical ownership, review designs and implementations, provide constructive feedback, and mentor engineers through challenging technical decisions.

• Maintain close relationships with consultants and users, support product rollout and adoption, and communicate technical risks and decisions clearly.

• Partner with relevant domain and control authorities to meet quality standards and risk management requirements.

• Take hands-on responsibility for implementation, code reviews, debugging, and production investigations when needed.

Requirements

The ideal candidate is an experienced software engineer and technical leader who can combine strong implementation skills with sound architectural judgment, delivery accountability, and the ability to develop independent engineering teams.

• Bachelor's degree in Computer Science, Engineering, or a related field.

• At least 6 years of relevant experience in software engineering, data-intensive systems, platform engineering, or a closely related discipline.

• At least 2 years of experience in a technical lead, staff engineer, or similar role, with responsibility for technical direction, delivery ownership, and developing other engineers.

• Strong production software engineering skills, including the ability to inspect, debug, and improve existing implementations hands-on.

• Experience designing and operating cloud-based systems on Microsoft Azure or a comparable platform, including deployment, identity and access management, observability, and operational reliability.

• Strong understanding of SQL, data modeling, APIs, and cross-system integration.

• Demonstrated judgment in testing, data integrity, security boundaries, failure modes, and the evidence required before releasing changes.

• Practical experience using AI-assisted development tools, supported by a disciplined approach…