Spring Health aims to revolutionize mental healthcare by removing barriers to access and delivering personalized care through its clinically validated technology. The company seeks an Engineering Manager for its AI/ML Platform team to accelerate the delivery of cutting-edge improvements, scale core AI and ML platforms, and enable faster, safer, and more robust feature deployment.
Requirements
- 2-4+ years in a formal engineering management role. You have direct experience leading teams of 4+ engineers and a history of productionizing successful AI/ML platforms and solutions.
- 1+ years of experience iteratively building AI-empowered tools and ensuring they are operating safely and at scale. You have 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.
- 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. You have hands-on experience building, evaluating, and deploying machine learning models.
- Strong understanding of the modern AI/ML stack, including cloud services (AWS, GCP, Azure), container orchestration (Kubernetes), IaC (Terraform), and CI/CD systems.
- You are proficient in Python and have experience with LLM tools like LangGraph and LangSmith.
- Security and Privacy Awareness: We work with sensitive data - 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.
Responsibilities
- Provide Technical Leadership: Guide the team through complex architectural decisions across the full AI/ML stack, from our core ML infrastructure (e.g., model registry, CI/CD, feature stores) to LLM orchestration and observability.
- 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. You will help implement standard practices and patterns that make it easy to include safety guardrails for new applications.
- Drive Operational Excellence: Improve our MLOps and LLMOps capabilities. You will help establish robust, automated monitoring for model performance, latency, and cost; define SLOs for platform components; and build the CI/CD pipelines that enable teams to deploy and iterate on models safely and quickly.
- Execute on Strategy and Drive Alignment: Break down large initiatives into clear, phased roadmaps. You will be a key partner for your product manager in navigating complex prioritization decisions and making strategic trade-offs.
- Manage Stakeholders and Communicate Progress: Build strong relationships and manage dependencies across the organization, including with Product, Member Experience, and Clinical teams. You'll track and communicate KPI-focused metrics that measure your platform's health, adoption rate, and impact on developer velocity.
- Lead a High-Performing Team: Foster a culture of psychological safety and continuous learning where engineers feel empowered to do their best work. You will attract, hire, and retain top-tier ML engineering talent.
- Drive Accountability and Performance: Set clear and ambitious goals and KPIs for your team. You will establish a rhythm of accountability through regular check-ins and performance reviews, addressing underperformance constructively while celebrating wins.
Other
- Candidates for this position must be based in the San Francisco Bay Area and be willing to commute 2-3 days a week to our office at 2 Embarcadero, San Francisco, CA
- Foster a culture of psychological safety and continuous learning where engineers feel empowered to do their best work.
- Set clear and ambitious goals and KPIs for your team.
- Actively mentor engineers to grow their technical and soft skills.
- Demonstrated ability to collaborate with product management and other cross-functional partners in an outcome-driven environment.
