Product Engineering Leader (Senior Manager/Associate Director)!

Product Engineering Leader (Lifesciences domain)!

Role Purpose

Lead the Product Engineering function at MaxisAI, responsible for architecting, building, and maintaining the core clinical AI platform. This role owns the full engineering lifecyclefrom architecture and development to CI/CD, quality, and technical debt managementdelivering scalable, secure, and enterprise-grade software.

Reporting Structure

Reports To: VP Product And Technology

Works Closely With:

• Product Leader
• AI Engineering Lead
• PMO Lead
• DevOps / Platform Engineering Teams
• Client Services

Key Responsibilities

• Own architecture, engineering delivery, and technical quality across all MaxisAI product components.
• Lead, mentor, and grow a high-performing engineering team including frontend, backend, and platform engineers.
• Drive adoption of AI-assisted development tools (Claude Code, GitHub Copilot, Cursor) across the engineering team.
• Establish and enforce engineering standards: code review, testing, CI/CD, observability, and security practices.
• Own the technical roadmap and engineering capacity planning aligned to product and business priorities.
• Collaborate with Product Leader to refine requirements, estimate effort, and commit to delivery timelines.
• Oversee platform reliability, performance, and availability across multi-tenant and single-tenant deployments.
• Manage vendor and third-party technology relationships relevant to engineering.
• Ensure adherence to GxP software validation, data security, and compliance requirements.
• Conduct architecture reviews, technology evaluations, and build-vs-buy decisions.
• Own technical debt management and continuous engineering improvement programs.
• Partner with the Director of Delivery Excellence to align engineering velocity with SDLC standards.

Required Experience

• 10+ years in software engineering, with at least 4 years in an engineering leadership role.
• Hands-on background in backend (Node.js, Python), frontend (React), and cloud-native architectures (AWS preferred).
• Experience leading engineering teams in B2B SaaS, healthtech, or clinical tech environments.
• Strong understanding of CI/CD pipelines, DevOps practices, and infrastructure as code.
• Track record of delivering high-quality, scalable systems under iterative Agile delivery models.
• Experience integrating or building AI/ML-powered products or workflows.

Preferred Background

• Experience with GxP software validation or FDA-regulated system delivery.
• Familiarity with clinical data standards (FHIR, CDISC, HL7).
• Exposure to AWS Bedrock, LLM orchestration, or agentic AI architectures.
• Prior experience in a startup or scale-up technology environment.

Success Measures First 12 Months

• Establish team engineering standards and SDLC practices within 30 days.
• Achieve >75% automated test coverage within 6 months.
• Reduce production incidents by 30% within 12 months.
• Drive AI tool adoption to >80% of the engineering team within 6 months.
• Deliver on-time engineering milestones with >85% predictability

Candidates with prior exposure in the Pharma/Biotech/CRO/Medical Devices sector will be given a preference.