Staff Full Stack Engineer (Hybrid)

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

As Staff FullStack 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. This is a hybrid role based at our Pittsburgh, PA headquarters.

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 3DCC 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

Prior direct customer-facing experience is not required, but candidates must demonstrate confidence and readiness to join customer calls when needed - troubleshooting issues, explaining API integration capabilities, etc.

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