AI Engineering Lead
Employment Type: Full-Time
Location: Remote - Must be local to Bay Area, CA
About the Role
We are seeking an AI Engineering Lead to help design, build, and scale enterprise-grade B2B SaaS products with deep AI foundations in the healthcare space. This role is hands-on and builder-focused, requiring heavy experience designing and shipping AI-powered systems that are secure, scalable, and production-ready. Success in this role means owning AI-driven product architecture while collaborating closely across front-end, backend, and product teams in a fast-moving, high-growth environment.
Key Responsibilities
Lead the design and implementation of AI-powered application features used in enterprise B2B environments
Build and scale production-grade AI systems with a focus on reliability, security, and performance
Work hands-on with modern AI tooling and workflows (e.g., Claude Code, Cursor, agent frameworks)
Architect systems that integrate AI capabilities into full-stack applications (front-end + backend)
Partner closely with Product, Design, and Engineering leadership to translate complex business needs into AI-driven solutions
Set technical standards and best practices for AI development, experimentation, and deployment
Mentor and guide engineers contributing to AI and application-layer development
Collaborate with backend teams using Node.js and AWS to support scalable, secure AI workloads
Required Qualifications
8+ years of software engineering experience with significant hands-on experience building AI-powered systems
Proven experience building and shipping AI-driven features in B2B enterprise applications
Strong experience working with modern AI development tools (e.g., Claude Code, Cursor, AI copilots, agent-based workflows)
Expertise designing secure, scalable systems for enterprise or regulated customers
Solid experience with cloud platforms (AWS) supporting AI workloads
Proficiency in full-stack development with strong front-end experience (React, TypeScript)
Experience integrating AI capabilities into production user-facing applications
Strong communication skills and comfort operating in startup or high-growth environments
Preferred Qualifications
Experience working in healthcare technology or regulated environments (HIPAA)
Deep experience with AI-driven user experiences or data-intensive applications
Background building internal AI tooling, automation, or developer platforms
Experience balancing experimentation with production hardening for AI systems
Prior ownership of system scalability, performance, or observability in AI-enabled products