Full Stack Engineer

Staff Fullstack Engineer

Most staff engineering roles ask you to choose between architecture and code, or between engineering and customers. This one doesn't.

As a Staff Full Stack Engineer, you'll set the technical direction for how Gather AI's platform integrates with the world, while staying hands-on with the code, infrastructure, and Kubernetes clusters that run it. You'll lead the shift from ad hoc, growth-era integration patterns to enterprise-grade standards, elevate a live customer-facing solution alongside the engineer already driving it, and become the single US-based point of contact who turns customer requirements into shipped, scoped engineering work.

What You'll Do

• Architect and build across distributed systems, APIs, integrations, and infra shipping your own code with performance, fault-tolerance, and horizontal scale as first-class design concerns.
• Own the platform's non-functional bar by setting explicit targets for scalability, reliability, availability, latency, performance, security, and observability, and holding the full stack to them.
• Partner with team members on multiple projects like MHEV, Drone and 3
  
  DCC to elevate and deliver solutions in technical design and take new requirements to production at high SDLC standards (testable, observable, well-scaled, tuned DB access).
• Decompose overloaded APIs into well-bounded services and introduce data-access abstractions that control DB connections and improve scalability.
• Retire reliability and compliance debt (e.g., PostgreSQL upgrades), stand up production observability metrics and alerts, and reduce delivery friction with CI/CD and AI-assisted delivery.
• Serve as the US-based single point of contact for fullstack work, partnering with Customer Success to turn customer requirements into clear, well-scoped engineering.
• Mentor senior engineers and raise the bar on engineering practices across backend and infrastructure.

What You'll Need

• 8+ years building and operating production software, with a track record of taking large, stateful systems to enterprise-grade scale and reliability
• Deep hands-on experience with Python, Go and Node.js, PostgreSQL at production scale, and Kubernetes on Azure, from architecture through independent production debugging
• Depth in APIs and integrations across internal service-to-service and external partner integrations: REST, protobuf, messaging, and OAuth, plus secure integration protocols across HTTP, SFTP, email, and IPSec, designed for resilience and secure data exchange
• Deep grasp of non-functional design: scalability, availability and failure modes, latency budgets, caching, and security as first-class concerns, not afterthoughts
• Solid, hands-on CI/CD: building and owning automated build, test, and deployment pipelines that make delivery fast and safe
• Production-grade observability: instrumenting logs, metrics, and traces, and using them (with SLIs/SLOs and incident response) to keep systems healthy
• Practical AI-assisted engineering, using tools such as Claude across the SDLC with sensible guardrails
• Establishing best practices that raise team's engineering standard
• Comfortable running customer-facing technical conversations and translating ambiguous requirements into scoped engineering work

Nice to Have

• Domain experience in logistics, warehouse management systems, or robotics-adjacent platforms
• Experience taking systems multi-region with read-write replication or geo-distribution
• Experience adopting AI across the software development lifecycle, including GenAI code-validation guardrails