GovCloud Distributed Systems Software Engineer

Leadout Capital; San Francisco (CA); On-site; USD 190,000 - 250,000; Full time

Job summary

Leadout Capital seeks an experienced Distributed Systems Software Engineer - GovCloud (Senior/Lead) to join our public cloud engineering team in the U.S. You will build and maintain large-scale distributed systems, ensure high availability, and integrate AI-driven tooling into production workflows.

The role emphasizes a strong backend focus with proficiency in Java, Golang, Python, or Ruby, and experience with Kubernetes, Terraform, and AI tools. Security clearances and U.S.

Qualifications

• A related technical degree required.
• 5+ years backend software development experience.
• Deep knowledge of programming in Java, Golang, Python, or Ruby.
• Experience owning and operating multiple instances of a critical service.
• Experience with Agile development methodology and Test Driven Development.
• Experience with critical infrastructure services including monitoring, alerting, logging, and reporting applications.
• Experience with distributed database systems and relational databases like Postgres is a plus.
• Demonstrated AI-first approach to engineering and AI tools in workflows.

Responsibilities

• Deliver cloud infrastructure automation tools, frameworks, workflows, and validation platforms on public cloud platforms (AWS, GCP, Azure, or Alibaba).
• Design, develop, debug, and operate resilient distributed systems across data centers.
• Build production-grade software with AI components into development workflows.
• Use and contribute to open source technologies.
• Develop Infrastructure-as-Code using Terraform.
• Write microservices on Kubernetes, Docker, Mesos.
• Architect complex systems where AI agents integrate with human workflows.
• Contribute to the shared system context documenting designs and standards.
• Critically evaluate code (human or AI-generated) for quality and security.
• Participate in on-call rotations to maintain service availability.

Skills

Backend dev

Distributed systems

AI-first approach

Cloud platforms

Agile / TDD

Education

Related technical degree

Tools

Java

Golang

Python

Ruby

Job description

Must be a U.S. Citizen operating on U.S. Soil with ability to meet customer and government screening standards applicable to this role, including a Criminal Justice Information Services screening with fingerprint scan. Due to the citizenship requirement for this role, which supports U.S. federal, state, and/or local government customers, citizenship will be verified through two of the following REAL ID Act documents: U.S. Passport, Passport Card, REAL Driver's License, Global Entry Card, U.S. Government CAC/PIV.

Distributed Systems Software Engineer - GovCloud (Senior/Lead)

Our Public Cloud engineering teams are responsible for innovating and maintaining a large scale distributed systems engineering platform that ships hundreds of features to production for tens of millions of users across all industries every day. Our users count on our platform to be highly reliable, lightning fast, supremely secure, and to preserve all of their customizations and integrations every time we ship. You will need deep experience with concurrency, large scale systems, proficiency with solving real-world data management challenges, a strong understanding of how to craft solutions that are highly available, and a proven ability to design, develop, and optimize the core back-end systems. This role requires advanced prompt engineering skills — the ability to write precise, structured prompts and cultivate the system context that makes AI outputs reliable, secure, and production-ready.

Your Impact:

• Deliver cloud infrastructure automation tools, frameworks, workflows, and validation platforms on our public cloud platforms such as AWS, GCP, Azure, or Alibaba
• Designing, developing, debugging, and operating resilient distributed systems that run across thousands of compute nodes in multiple data centers
• Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow by pushing the boundaries of AI development tools (Cursor, Windsurf, Claude, OpenAI API) to deliver secure, optimized, and high-quality code.
• Using and contributing to open source technology (Spinnaker, Zookeeper, etc.)
• Developing Infrastructure-as-Code using Terraform
• Writing microservices on containerization frameworks such as Kubernetes, Docker, Mesos
• Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
• Contribute to building and maintaining the shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably.
• Critically evaluate code (Human or AI-generated) for correctness, quality, security, and performance
• Resolving complex technical issues and drive innovations that improve system availability, resilience, and performance
• Eat, sleep, and breathe services. You have experience balancing live-site management, feature delivery, and retirement of technical debt
• Participate in the team’s on-call rotation to address complex problems in real-time and keep services operational and highly available

Required Skills:

• A related technical degree required
• 5+ years backend software development experience
• Deep knowledge of programming in Java, Golang, Python, or Ruby
• Experience owning and operating multiple instances of a critical service
• Experience with Agile development methodology and Test Driven Development
• Experience with critical infrastructure services including, monitoring, alerting, logging, and reporting applications
• Experience with distributed database system and relational databases like postgres is a plus.
• A demonstrated, genuine AI-first approach to engineering. Using AI to move faster, build fluency across the stack, and contribute well beyond your core specialty.
• Experience using AI tools (e.g., Claude Code, GitHub Copilot, Codex, Cursor, etc.) in development workflows
• Advanced prompt engineering skills and the ability to write precise, structured prompts and cultivate the system context that makes AI outputs reliable, secure, and production-ready.