Fieldguide
Staff Software Engineer, App Platform
San Francisco, CA or Remote (USA) · Staff+
Sponsorship not specifiedDetected 67 days ago
Distributed SystemsAWSCloud PlatformsKubernetesPlatform EngineeringLLMsAccountingCommunication
About the role
- This is the platform on which every product surface and AI agent at Fieldguide is built.
- You will operate as a technical leader across teams, defining standards and reducing complexity for product, AI, and infrastructure engineers.
- Your work will directly shape how Fieldguide can ship quickly for our largest enterprise customers while keeping our systems reliable and scalable.
Responsibilities
- Lead the design and evolution of Fieldguide's core platform services, including the foundational systems, APIs, and shared primitives that every product surface and agent depends on
- Build platform capabilities that compound the leverage of product and AI engineers, turning hard problems into reusable building blocks
- Partner directly with product, design, and AI engineering leaders to understand customer needs and translate them into platform investments
- Drive cross-team initiatives that improve product velocity, system reliability, and consistency across the application
- Own the standards for service design, data modeling, and platform integration patterns used across Fieldguide
- Maintain and evolve the internal developer platform that supports the team, including deployment tooling, and agentic engineering capabilities
- Deep experience designing APIs, services, and shared systems that other engineers build on top of
- Experience designing platforms that support both multi-tenant SaaS and single-tenant enterprise deployments
- Lovable - Deliver happiness and 11-star experiences
- Win-win - Create mutual value and earn trust for life
Requirements
- 10+ years of experience in software engineering, with significant time spent building product-facing platforms or foundational application services
- Strong product instincts and a track record of shipping platform capabilities that unlocked meaningful customer outcomes
- Track record of operating as a technical leader across multiple teams without owning them directly
- Strong software engineering fundamentals and the ability to contribute to and review complex codebases
- Experience as a founding or early platform engineer at a vertical SaaS or enterprise AI company
Nice to have
- Strong fluency with modern cloud platforms (AWS preferred), Kubernetes, and distributed systems
Compensation
- Competitive compensation with equity
Benefits
- Competitive compensation with equity
- Comprehensive health and wellness benefits
- Flexible time off and work schedules
- Wellness benefits starting on your first day
- Excellent judgment on what to build into the platform, what to leave to product teams, and what to buy
Company info
- Fieldguide is establishing a new state of trust for global commerce and capital markets by automating and streamlining the work of assurance and audit practitioners-specifically in cybersecurity, privacy, and financial audits. We build software for the people who enable trust between businesses.
- We're based in San Francisco, CA, and built remote-first. We're backed by Goldman Sachs Alternatives, Bessemer Venture Partners, 8VC, Floodgate, Y Combinator, and more. Over 50 of the top 100 accounting and consulting firms trust Fieldguide to power mission-critical work.
- Fieldguide is establishing a new state of trust for global commerce and capital markets by automating and streamlining the work of assurance and audit practitioners-specifically in cybersecurity, privacy, and financial audits.
- We build software for the people who enable trust between businesses.
- We're based in San Francisco, CA, and built remote-first.
- We're backed by Goldman Sachs Alternatives, Bessemer Venture Partners, 8VC, Floodgate, Y Combinator, and more.
- Over 50 of the top 100 accounting and consulting firms trust Fieldguide to power mission-critical work.
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This listing is sourced directly from Fieldguide's careers page and normalized into a canonical job model.