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ResolveAI

Software Engineer, Infrastructure Security

San Francisco, California, United States

Location
San Francisco, California, United States
Work
On-site
Employment
Full-time
Level
Not stated
Function
Security
Pay
Not stated
Posted
8 months ago

About the role

About Resolve AI

  • Software maintenance and production troubleshooting have become a massive tax of engineering velocity. Resolve AI is solving this by building a transformative, truly autonomous AI Production Engineer that investigates and fixes complex system issues end-to-end.
  • Our founders (Spiros Xanthos and Mayank Agarwal) are the core creators of OpenTelemetry and led Splunk Observability. They have had 2 successful exits to Splunk and VMware.
  • We’ve raised over $190M from top-tier investors including Lightspeed, Greylock, DST, Unusual Ventures, and individual backers such as Jeff Dean (Chief Scientist, Google DeepMind), Thomas Dohmke (CEO, GitHub), Matt Garman (CEO, AWS), Reid Hoffman (Founder, LinkedIn), and Fei-Fei Li (Professor, Stanford).

What You’ll Do

  • Own security across the Resolve AI platform, spanning application security, cloud infrastructure, internal services, integrations, and agent execution.
  • Design security mechanisms that work with autonomous systems, enabling agents to take action safely, audibly, and within well-defined boundaries.
  • Partner closely with engineers across platform, infra, and product to shape secure system designs early, not retroactively.
  • Build security directly into how we ship software: automation in CI/CD, guardrails in infrastructure, and defaults that scale as the company grows.
  • Evaluate and improve how we handle identity, permissions, and access across customers, tools, and environments.
  • Stay ahead of emerging risks related to AI-driven systems and propose concrete, engineering-led mitigations.
  • Help Resolve AI meet the expectations of enterprise customers by clearly articulating our security posture and participating in technical security conversations when needed.
  • Set the foundation for how security is practiced at Resolve: pragmatic, high-signal, and aligned with how real systems operate.

What We’re Looking For

  • A Bachelor's degree in Computer Science or a closely related technical field is required for this position.
  • Experience securing modern production systems, including web applications, cloud infrastructure, and internal services.
  • A strong engineering background, with hands-on experience writing production code and building automation (Python required; other languages welcome).
  • Comfort working across cloud environments (AWS, GCP, or Azure), including IAM, networking, and infrastructure-as-code.
  • Practical experience with threat modeling, vulnerability management, and incident response and good instincts for what actually matters in production.
  • The ability to operate in ambiguity, make tradeoffs, and move quickly without losing rigor.
  • Clear communication skills and the judgment to explain risk in a way that builds trust with engineers, leadership, and customers.
  • Curiosity and a customer-oriented mindset: you want to understand how Resolve is used in the real world and secure it accordingly.

Nice to Have

  • Experience securing AI or ML-driven systems, including familiarity with risks unique to LLMs or agentic workflows.
  • Background building or integrating security tooling, especially where automation or scale was a core challenge.
  • Exposure to regulated environments or enterprise security reviews.
  • Experience designing systems with privacy-first principles such as data minimization, isolation, and anonymization.

We are an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender, gender identity, sexual orientation, protected veteran status, disability, age, and other characteristics protected by law.

Source

Posted by ResolveAI on their own hiring page, jobs.ashbyhq.com. OptiTalent shows it as published, read 07 Nov 2026 02:03 UTC; the original is the reference.

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