Spring Health
Engineering Manager - AI & ML Infrastructure
Spring Health, San Francisco, California, United States, 94199
Overview
Engineering Manager - AI & ML Infrastructure at Spring Health. You will lead the AI/ML Platform team to accelerate the delivery of cutting-edge improvements that remove barriers to mental health, building and scaling core AI and ML platforms used by product teams. This is a hybrid role based in San Francisco, with 2-3 days in the office weekly at 2 Embarcadero Ctr. What you’ll do
Provide Technical Leadership:
Guide architectural decisions across the full AI/ML stack, including core infrastructure (model registry, CI/CD, feature stores), LLM orchestration, and observability. Champion AI Trust & Safety:
Translate clinical norms, fairness, and transparency into technical controls and guardrails in collaboration with the AI Trust team. Drive Operational Excellence:
Improve MLOps/LLMOps, implement automated monitoring for performance, latency, and cost, define SLOs, and build CI/CD pipelines for safe and rapid model deployment. Execute on Strategy and Drive Alignment:
Break initiatives into phased roadmaps and partner with product management on prioritization and trade-offs. Manage Stakeholders and Communicate Progress:
Build relationships across Product, Member Experience, and Clinical teams; track KPI-focused metrics on platform health, adoption, and developer velocity. Lead a High-Performing Team:
Foster psychological safety, attract and retain ML engineering talent, and promote continuous learning. Drive Accountability and Performance:
Set goals and KPIs, establish regular check-ins and performance reviews, and address underperformance constructively. Coach and Develop Talent:
Mentor engineers and use career ladders to create development plans aligned with team and company goals. What success looks like
Velocity & Safety:
Reusable AI safety guardrails and platform components reduce time to ship new AI features. LLM Platform Maturity:
CI/CD for prompts, automated monitoring/alerting, A/B testing; infrastructure for RAG, fine-tuning, and LLM memory. ML Platform Maturity:
Centralized model registry, automated deployment pipelines, and standardized development environments. Platform Adoption:
Increased usage of models and features on the core infrastructure. What you’ll bring
Proven Leadership:
2-4+ years in engineering management; experience leading teams of 4+ engineers and delivering AI/ML platforms. LLM Operations Expertise:
1+ year building AI-powered tools at scale with LangGraph, LangSmith, and safe-guardrails. Machine Learning Expertise:
5+ years in software or ML engineering, with experience deploying ML models. Technical Proficiency:
Cloud services (AWS, GCP, Azure), Kubernetes, Terraform, CI/CD; Python; familiarity with LangGraph/LangSmith. Strategic Mindset:
Collaboration with product management in outcome-driven environments. Project Management Skills:
Experience delivering complex, multi-month technical projects. Security and Privacy Awareness:
Work with sensitive data; healthcare experience is preferred. Compensation and Benefits
The target base salary range is $159,100 – $213,565 and includes stock options and benefits. Pay may vary by experience, location, and other factors. We review compensation annually using external benchmarks to ensure competitiveness. Benefits
Benefits are subject to plan requirements and eligibility. Highlights include: Medical, dental, and vision benefits starting on day one; One Medical accounts; HSA/FSA with company contributions. 401(k) with employer match up to 2%. No-cost visits with Spring Health network providers for you and dependents. PTO, vacation, sick leave, and holidays. Parental leave after six months (18 weeks birthing, 16 weeks non-birthing). Wellness programs (Noom weight management, fertility support with Carrot, Wellhub for wellness, BrightHorizons for child and elder care). Professional development reimbursement up to $1,000/year. Donation matching up to $200/year. Equal Opportunity
Spring Health is an equal opportunity employer. We do not discriminate on protected characteristics and provide reasonable accommodations as needed. We encourage applicants from diverse backgrounds to apply.
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Engineering Manager - AI & ML Infrastructure at Spring Health. You will lead the AI/ML Platform team to accelerate the delivery of cutting-edge improvements that remove barriers to mental health, building and scaling core AI and ML platforms used by product teams. This is a hybrid role based in San Francisco, with 2-3 days in the office weekly at 2 Embarcadero Ctr. What you’ll do
Provide Technical Leadership:
Guide architectural decisions across the full AI/ML stack, including core infrastructure (model registry, CI/CD, feature stores), LLM orchestration, and observability. Champion AI Trust & Safety:
Translate clinical norms, fairness, and transparency into technical controls and guardrails in collaboration with the AI Trust team. Drive Operational Excellence:
Improve MLOps/LLMOps, implement automated monitoring for performance, latency, and cost, define SLOs, and build CI/CD pipelines for safe and rapid model deployment. Execute on Strategy and Drive Alignment:
Break initiatives into phased roadmaps and partner with product management on prioritization and trade-offs. Manage Stakeholders and Communicate Progress:
Build relationships across Product, Member Experience, and Clinical teams; track KPI-focused metrics on platform health, adoption, and developer velocity. Lead a High-Performing Team:
Foster psychological safety, attract and retain ML engineering talent, and promote continuous learning. Drive Accountability and Performance:
Set goals and KPIs, establish regular check-ins and performance reviews, and address underperformance constructively. Coach and Develop Talent:
Mentor engineers and use career ladders to create development plans aligned with team and company goals. What success looks like
Velocity & Safety:
Reusable AI safety guardrails and platform components reduce time to ship new AI features. LLM Platform Maturity:
CI/CD for prompts, automated monitoring/alerting, A/B testing; infrastructure for RAG, fine-tuning, and LLM memory. ML Platform Maturity:
Centralized model registry, automated deployment pipelines, and standardized development environments. Platform Adoption:
Increased usage of models and features on the core infrastructure. What you’ll bring
Proven Leadership:
2-4+ years in engineering management; experience leading teams of 4+ engineers and delivering AI/ML platforms. LLM Operations Expertise:
1+ year building AI-powered tools at scale with LangGraph, LangSmith, and safe-guardrails. Machine Learning Expertise:
5+ years in software or ML engineering, with experience deploying ML models. Technical Proficiency:
Cloud services (AWS, GCP, Azure), Kubernetes, Terraform, CI/CD; Python; familiarity with LangGraph/LangSmith. Strategic Mindset:
Collaboration with product management in outcome-driven environments. Project Management Skills:
Experience delivering complex, multi-month technical projects. Security and Privacy Awareness:
Work with sensitive data; healthcare experience is preferred. Compensation and Benefits
The target base salary range is $159,100 – $213,565 and includes stock options and benefits. Pay may vary by experience, location, and other factors. We review compensation annually using external benchmarks to ensure competitiveness. Benefits
Benefits are subject to plan requirements and eligibility. Highlights include: Medical, dental, and vision benefits starting on day one; One Medical accounts; HSA/FSA with company contributions. 401(k) with employer match up to 2%. No-cost visits with Spring Health network providers for you and dependents. PTO, vacation, sick leave, and holidays. Parental leave after six months (18 weeks birthing, 16 weeks non-birthing). Wellness programs (Noom weight management, fertility support with Carrot, Wellhub for wellness, BrightHorizons for child and elder care). Professional development reimbursement up to $1,000/year. Donation matching up to $200/year. Equal Opportunity
Spring Health is an equal opportunity employer. We do not discriminate on protected characteristics and provide reasonable accommodations as needed. We encourage applicants from diverse backgrounds to apply.
#J-18808-Ljbffr