Staff Software Engineer, App Platform

Remote from: USA
Salary, yearly, USD: 210,000 - 265,000
Department: Software Engineering
Employment type: Full Time,
Job posted: 16 May 2026
Apply before: 16 Jun 2026
Experience level: Senior
Views / Applies: 10 / 1

Powering the future of trust by amplifying the advisory and audit engagement experience for CPA firms and their clients.

Computer Software
2019

AI Summary

Fieldguide is seeking a Staff Software Engineer for their App Platform team to design and build foundational platform services that power their audit and assurance software. The role involves leading cross-team technical initiatives, defining architecture for multi-environment deployments, and mentoring engineers. The ideal candidate has 10+ years of experience, deep expertise in cloud platforms (AWS), Kubernetes, and distributed systems, and a track record of building product-facing platforms. This is a remote-first role based in San Francisco, offering competitive compensation and comprehensive benefits.

Job Complexity

Easy Hard

AI Insight The role requires 10+ years of experience, technical leadership across teams, and expertise in complex platform engineering, making it highly challenging but not the hardest due to the availability of similar senior roles.

Salary Analysis

AI Insight The offered salary range of $210,000 - $265,000 is competitive for a Staff Platform Engineer role, aligning well with the market median of $237,500. This reflects the seniority and impact of the position.

Key Skills

Platform Engineering Kubernetes AWS Distributed Systems API Design Microservices SaaS Enterprise Software Technical Leadership AI

Cover Letter Sample

I am excited to apply for the Staff Software Engineer, App Platform role at Fieldguide. With over 10 years of software engineering experience, including significant time building product-facing platforms, I am confident in my ability to lead the design and evolution of your core platform services.

My expertise in AWS, Kubernetes, and distributed systems, combined with a track record of driving cross-team initiatives, aligns with your need for a technical leader who can define standards and reduce complexity. I have a strong product instinct and have successfully shipped platform capabilities that unlocked meaningful customer outcomes.

I am particularly drawn to Fieldguide's mission of automating assurance and audit work, and I am eager to contribute to a platform that powers AI-native products and supports both multi-tenant SaaS and single-tenant deployments.

Thank you for considering my application. I look forward to the opportunity to discuss how I can help Fieldguide scale its platform and deliver exceptional value to customers.

Possible Interview Questions

Can you describe a platform capability you designed that significantly improved the velocity of product teams? How did you measure success?

At my previous company, I led the creation of a shared service for feature flags and configuration management. This allowed product teams to roll out features gradually and roll back quickly without redeploying. Success was measured by the reduction in deployment-related incidents (down 40%) and the time to deliver new features (shortened by 30%).

How do you decide what to build into the platform versus leaving to product teams?

I follow the principle of building platform capabilities that provide leverage across multiple teams. If multiple product teams independently solve the same problem, it's a candidate for a platform service. I also consider the cost of building and maintaining versus buying, and whether the capability is core to our competitive advantage.

Describe your experience with Kubernetes in production. How did you handle scaling and reliability challenges?

I have managed Kubernetes clusters for a SaaS platform serving millions of users. We implemented horizontal pod autoscaling based on custom metrics, used cluster autoscaler for node scaling, and set up pod disruption budgets for high availability. For reliability, we used readiness probes, implemented circuit breakers, and had a robust monitoring and alerting system using Prometheus and Grafana.

How would you approach designing a platform that supports both multi-tenant SaaS and single-tenant enterprise deployments?

I would design the platform with a clear separation between core services and deployment-specific configurations. Using infrastructure-as-code, we can define different deployment profiles. For multi-tenancy, we use tenant isolation via namespaces and resource quotas. For single-tenant, we package the platform as a deployable unit with its own database and compute resources. The key is to abstract the common logic and use feature flags for enterprise-specific customizations.

Tell me about a time you mentored senior engineers to raise the bar for platform engineering. What approach did you take?

I established a platform engineering guild where we held weekly sessions to discuss design patterns, code reviews, and incident post-mortems. I encouraged senior engineers to lead design documents and provided feedback on architecture decisions. I also instituted pair programming for complex tasks and created a mentorship program where experienced engineers guided newer team members. This led to a measurable improvement in code quality and a reduction in onboarding time for new hires.

About Us

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.

About the Role

As a Staff Platform Engineer at Fieldguide, you will design and build the foundational platform that powers Fieldguide, including core platform services and tooling that make it fast, safe, and consistent to deliver new capabilities to customers. 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.

What You’ll Own

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
Define the architecture for how new product capabilities get delivered across our SaaS, enterprise single-tenant, and government-cloud environments
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
Mentor senior and mid-level engineers across the org and raise the bar for platform engineering at Fieldguide

Who You Are

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
Deep experience designing APIs, services, and shared systems that other engineers build on top of
Strong fluency with modern cloud platforms (AWS preferred), Kubernetes, and distributed systems
Track record of operating as a technical leader across multiple teams without owning them directly
Excellent judgment on what to build into the platform, what to leave to product teams, and what to buy
Strong software engineering fundamentals and the ability to contribute to and review complex codebases
Excellent written and verbal communication, with the ability to drive alignment across engineering, product, and design
High agency and a bias toward owning problems end-to-end

Bonus Points

Experience building platforms that power AI-native products, including agent frameworks, model orchestration, or LLM-powered application surfaces
Experience designing platforms that support both multi-tenant SaaS and single-tenant enterprise deployments
Experience as a founding or early platform engineer at a vertical SaaS or enterprise AI company