About the Role
At Spring Health, we’re on a mission to revolutionize mental healthcare by removing every barrier that prevents people from getting the help they need, when they need it. Our clinically validated technology, Precision Mental Healthcare, empowers us to deliver the right care at the right time—whether it’s therapy, coaching, medication, or beyond—tailored to each individual’s needs.
We are actively seeking a Staff AI Security Engineer to join our team. Reporting to the CISO, you will define and evolve our AI security strategy to protect highly sensitive mental health data across both product and corporate environments. This is a hybrid role based in San Francisco, with an expectation to be in the office 2–3 days per week at our 44 Montgomery Street location. Candidates must be based in the San Francisco metro area or able to relocate independently within 90 days of their start date. Occasional travel will be required for team on-sites.
What you’ll do
- Define and evolve our AI security strategy to protect highly sensitive mental health data across both product and corporate environments
- Lead secure design and threat modeling for AI systems including LLMs, agentic workflows, and retrieval pipelines
- Identify and mitigate risks such as prompt injection, data exfiltration, model abuse, and privilege escalation
- Build scalable AI security guardrails and tooling that enable safe experimentation across engineering and business teams
- Establish AI-specific governance frameworks covering identity, access control, auditability, and observability
- Take ownership of and lead our AI Red Team to proactively identify vulnerabilities
- Design and implement AI observability pipelines to detect anomalous model behavior and policy violations in near real-time
- Develop and operationalize AI incident response playbooks to ensure rapid containment of security events
- Partner with product and engineering teams to enable responsible AI innovation in a hyper-growth environment
- Champion a culture of secure AI development by mentoring engineers and defining high standards for the organization
What success looks like in this role
- 80% of new AI product features are threat modeled prior to GA
- 80% of AI features are tested by the AI Red Team or equivalent adversarial testing before GA
- Achieve >=70% coverage of production AI features with automated LLM vulnerability testing
- Grow participation in the AI Red Team by 10% YoY
- Develop AI incident response playbooks and conduct at least one AI-focused tabletop or live simulation per year
What you’ll bring
- 10+ years experience in a software engineering discipline, with at least 5+ years focused on security
- Hands-on experience securing AI/ML systems, including practical AI red teaming against LLMs, agentic workflows, or RAG systems
- Experience developing or implementing automated LLM vulnerability testing for prompt injection and data exfiltration
- Strong foundation in application security principles, threat modeling, secure design, and identity and access control
- Demonstrated ability to build tools and automation with a developer mindset
- Experience influencing senior engineers and cross-functional stakeholders across product, legal, and compliance
- Proven track record of mentoring engineers and cultivating a strong security culture across an organization
- Strong working knowledge of modern developer tooling, CI/CD pipelines, and git-based collaboration
- Ability to operate in ambiguity and translate emerging AI risks into pragmatic, scalable security controls
- Deep personal ownership and a passion for advancing AI security through continuous learning