openleverjobgether
Staff Software Engineer, Developer Platform
Jobgether
LocationUS
EmploymentFull-time
Posted2026-08-26T05:03:37.642000+00:00
Last observed2026-08-26 21:51:40.410433
Job idjobgether-jobgether:lever:64589b97-8bdb-4175-a130-713e58183b0c
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Software Engineer, Developer Platform based in United States. This is a high-impact staff-level engineering role focused on building the internal platform that enables developers to ship secure software at scale. You’ll own significant areas across monorepo CI/CD, shared build infrastructure, and agentic AI tooling. The role combines deep technical execution with architectural leadership, platform strategy, and cross-functional influence. You’ll help reduce developer toil, improve delivery velocity, and create reliable, standardized paths from code changes to production. A major focus will be evolving engineering workflows to support AI-driven development while maintaining strong validation, security, and review standards. You’ll work closely with engineers across the organization, treating internal teams as platform customers and using data to improve their experience. This opportunity is ideal for a self-directed technical leader who thrives in ambiguity, enjoys solving complex infrastructure problems, and wants to shape the future of developer platforms. Own significant components of the Developer Platform, including monorepo CI/CD, agentic AI infrastructure, shared build systems, and related developer tooling. Define and influence technical direction by evaluating architectural tradeoffs, documenting designs, and aligning multiple engineering teams around scalable target architectures. Improve the speed, reliability, and developer experience of CI/CD pipelines so engineering teams can spend more time delivering software and less time troubleshooting builds. Help develop next-generation change workflows that extend beyond traditional pull-request models, including automated validation, trusted agent-driven changes, AI-assisted review, and safe auto-merge capabilities. Productionize agentic AI capabilities through observability, structured tracing, cost monitoring, debuggability, shared memory, and context-engineering patterns such as skills, tools, and memory. Consolidate fragmented build systems and create standardized platform blueprints that enable products to onboard quickly and move reliably into production. Partner with engineers across the organization to identify recurring sources of toil, automate manual processes, and anticipate developer needs before they become operational bottlenecks. Develop technical architecture documents that address reliability, security, performance, scalability, and maintainability requirements. Establish and improve developer productivity practices using metrics such as DORA and SPACE to measure engineering velocity and operational effectiveness. Mentor engineers, raise standards for system design and code reviews, and contribute as a senior technical voice across the engineering organization. Build stakeholder feedback loops and use internal engineering teams as customers to continuously improve platform capabilities and adoption. Requirements 8+ years of experience building and operating production services and platform infrastructure in modern cloud environments. Strong proficiency in Go (Golang), or demonstrated ability and willingness to ramp up quickly. Deep expertise in CI/CD systems, container-based orchestration, and the tooling required to operate large monorepos across build, test, and release workflows. Experience influencing technical direction across multiple engineering teams, including evaluating tradeoffs, retiring legacy systems, and establishing alignment around target architectures. Familiarity with production-grade Agentic AI or LLM-based automation, with an interest in context engineering, RAG, memory, and tool-calling at engineering-platform scale. Strong understanding of developer experience and engineering productivity, ideally including DORA or SPACE metrics and related instrumentation. Excellent communication and collaboration
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