Senior Manager, Engineering, AI & ML Infrastructure

• Provide Technical Leadership: Guide the team through complex architectural decisions across the full AI/ML stack
• Champion AI Trust & Safety: Work in close partnership with our AI Trust team to translate principles like clinical norms, fairness, and transparency into concrete technical controls and guardrails
• Drive Operational Excellence: Improve our MLOps and LLMOps capabilities
• establish robust, automated monitoring for model performance, latency, and cost
• define SLOs for platform components
• build CI/CD pipelines
• Execute on Strategy and Drive Alignment: Break down large initiatives into clear, phased roadmaps
• be a key partner for your product manager
• Manage Stakeholders and Communicate Progress: Build strong relationships and manage dependencies across the organization
• track and communicate KPI-focused metrics
• Lead a High-Performing Team: Foster a culture of psychological safety and continuous learning
• attract, hire, and retain top-tier ML engineering talent
• Drive Accountability and Performance: Set clear and ambitious goals and KPIs for your team
• establish a rhythm of accountability
• Coach and Develop Talent: Actively mentor engineers to grow their technical and soft skills
• create personalized development plans

• Proven Leadership: 2-4+ years in a formal engineering management role
• direct experience leading teams of 4+ engineers
• a history of productionizing successful AI/ML platforms and solutions
• LLM Operations Expertise: 1+ years of experience iteratively building AI-empowered tools and ensuring they are operating safely and at scale
• hands-on experience with the modern AI stack, including orchestration frameworks like LangGraph, observability tools like LangSmith, and best practices for prompt engineering and building safety guardrails
• Machine Learning Expertise: 5+ years of experience in software or machine learning engineering, with a background as a Senior MLE, SRE, or DevOps Engineer working on ML infrastructure
• hands-on experience building, evaluating, and deploying machine learning models
• Technical Proficiency: Strong understanding of the modern AI/ML stack, including cloud services (AWS, GCP, Azure), container orchestration (Kubernetes), IaC (Terraform), and CI/CD systems
• proficient in Python
• experience with LLM tools like LangGraph and LangSmith
• Strategic Mindset: Demonstrated ability to collaborate with product management and other cross-functional partners in an outcome-driven environment
• Project Management Skills: A history of successfully delivering complex, multi-month technical projects
• Security and Privacy Awareness: Ensuring that our pipelines and processes respect the trust of our customers and legal requirements is essential
• previous experience in a medical / health records industry is preferred

Previous experience in a medical / health records industry

• Health, Dental, Vision benefits start on your first day
• access to One Medical accounts
• HSA and FSA plans are also available, with Spring contributing up to $1K for HSAs
• Employer sponsored 401(k) match of up to 2%
• A yearly allotment of no cost visits to the Spring Health network of therapists, coaches, and medication management providers for you and your dependents
• competitive paid time off policies including vacation, sick leave and company holidays
• parental leave of 18 weeks for birthing parents and 16 weeks for non-birthing parents at 6 months tenure
• Access to Noom, a weight management program
• Access to fertility care support through Carrot, in addition to $4,000 reimbursement for related fertility expenses
• Access to Wellhub
• Access to BrightHorizons
• Up to $1,000 Professional Development Reimbursement a year
• $200 per year donation matching