Senior Software Engineer II, Search & Matching (Alma)

Spring Health is a global mental health company on a mission to eliminate every barrier to mental health. We're building a world where getting support is simple, personal, and built around the person, so care can continue through every job, move, health plan, and life stage.

Our AI-native platform helps us deliver personalized support across self-guided tools, coaching, therapy, medication management, and specialty care. With outcomes independently validated by JAMA Network Open and the Validation Institute, Spring Health reaches more than 170 million people worldwide through leading employers, health plans, and partners.

As an AI-native company, we believe technology should expand the reach, quality, and humanity of care. Every Spring Health team member is expected to use AI tools thoughtfully, apply human judgment to AI outputs, and keep building AI fluency in ways that support their role and our mission.

Reporting to the Engineering Manager - Search & Matching, this Senior Software Engineer II will be responsible for enhancing and optimizing the search and matching experience within Spring Health’s Alma product. As part of the Alma Search & Matching pod, you will help clients find the right provider and begin their care journey as quickly and seamlessly as possible. This role is  - is instrumental in eliminating barriers to mental health care by building high-quality, scalable experiences that connect clients with the right care.

Please note that 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.

• →Design and build scalable, high-quality software across complex, ambiguous problem areas in existing or new initiatives.
• →Lead group technical design sessions for large projects; routinely provide high-value feedback in design forums and architectural reviews.
• →Use AI to reason about system-level tradeoffs (scalability, performance, reliability) and integrate AI into team workflows—e.g., PR templates, debugging playbooks, and documentation—while ensuring all AI-assisted work meets rigorous quality standards.
• →Evaluate new AI tools and techniques; share learnings with the team and help establish standards for AI-assisted engineering.
• →Decompose significantly complex engineering problems into straightforward, well-scoped solutions.
• →Coordinate cross-group efforts, keeping everyone informed of appropriate context and progress.
• →Routinely provide perspective to identify and mitigate risks for others’ projects, not just your own.
• →Drive and complete projects end-to-end—sometimes more than one at a time—from conception through deployment and iteration.
• →Model engineering excellence: your code reviews are instructive, your designs are exemplary, and you proactively simplify and improve the code corpus.
• →Mentor engineers in both technical areas and career growth; motivate action by clearly explaining context, rationale, and roles.
• →Lead hypercare investigations and high-stakes bug responses; communicate progress quickly and clearly to stakeholders.
• →Design and build scalable search and matching capabilities for Spring Health’s Alma product, - improving how clients discover and connect with the right providers, with a focus on relevance, performance, and search quality.
• →Identify appropriate service boundaries and drive thoughtful architectural decisions about when and how to evolve capabilities out of the existing monolithic application.
• →Architect, build, and evolve backend services and APIs that power critical parts of Alma’s client search and matching experience, while contributing across the full stack as needed.

• Technical Excellence – Your architecture solutions are exemplary in terms of efficiency, stability, extensibility, and ability to evolve. Your software is robust in the presence of failures, scalable, and cost-effective.
• AI-Augmented Engineering – You actively integrate AI into your workflow and your team’s—evaluating tools, establishing quality standards, and helping teammates use AI effectively and responsibly.
• Cross-Team Impact – You solve complicated problems across service domains, coordinate with other teams as needed, and routinely reduce complexity for the engineers around you.
• Project Leadership – You drive and complete large, complex projects end-to-end with high stakeholder satisfaction—sometimes leading more than one initiative at a time.
• Engineering Excellence – Your code reviews make the overall codebase better. You proactively simplify, refactor, and improve—accounting for the full project lifecycle including continuous improvement.
• Mentorship & Org Health – You make your superpod more effective through significant contributions to individuals’ growth and engineering efficiency. Junior and mid-level engineers seek you out for guidance.
• Operational Leadership – You lead investigations calmly under pressure, with clear direction and communication to stakeholders throughout.

• 6–8+ years of professional software development experience
• Expertise in Python and Django for building scalable backend services and APIs, with strong proficiency in React
• Proven experience designing, building, and scaling complex full-stack systems, with a strong emphasis on backend architecture and development
• Uses AI to reason about system-level tradeoffs and integrates AI tools into team workflows—evaluates output critically and helps set quality standards for AI-assisted work
• Proven track record leading delivery of complex, multi-team technical projects
• Strong cross-functional collaboration skills; able to influence and align stakeholders across teams
• Demonstrated ability to mentor engineers on both technical skills and career growth
• Strong problem-solving skills with a focus on clean, scalable, maintainable architecture
• Embraces writing well-designed tests that accompany all code
• Proven experience with distributed systems and microservices architecture, including identifying appropriate service boundaries and making thoughtful architectural decisions about when and how to evolve capabilities out of a monolithic application
• Strong experience with data modeling and designing reliable data flows across services, with an understanding of consistency, performance, and scalability tradeoffs
• Experience designing and optimizing search experiences and search infrastructure, including indexing strategies, relevance and ranking, query performance, and search quality at scale

The target base salary range for this position is $207,000 - $233,000, and is part of a competitive total rewards package including stock options and benefits. Individual pay may vary from the target range and is determined by a number of factors including experience, location, internal pay equity, and other relevant business considerations. We review all employee pay and compensation programs annually using Radford Global Compensation Database at minimum to ensure competitive and fair pay.