Staff Full Stack Engineer

Gather AI$120K — $150K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 8+ years of experience in building and operating production software systems at scale
  • Proficient in Python, Go, Node.js, PostgreSQL, and Kubernetes on Azure
  • Expertise in API design and integrations with a focus on security and resilience
  • Strong understanding of non-functional design elements like scalability and availability
  • Hands-on experience with CI/CD processes and building automated deployment pipelines
  • Skilled in implementing production-grade observability for system health
  • Familiarity with AI tools for enhancing the software development lifecycle

Responsibilities

  • Design and develop across distributed systems, APIs, and infrastructure with performance and scalability as priorities
  • Set and uphold non-functional targets for system performance and reliability
  • Collaborate on various projects to ensure high technical standards and timely delivery
  • Refactor overloaded APIs into efficient microservices and implement data access abstractions
  • Address reliability and compliance challenges and enhance production observability
  • Act as the primary US-based contact for fullstack engineering work, aligning with customer needs
  • Coach and mentor other engineers to improve overall engineering practices

Benefits

  • Opportunity to work on a key team during a strategic growth phase
  • Engagement in both architectural design and hands-on coding tasks
  • Collaborative work with multiple departments like product, security, and customer success
  • Chance to influence the integration patterns of a live, customer-facing platform
  • Potential for impact on engineering standards and practices within the team
  • Support for using AI to optimize the software delivery workflow
Full Job Description
About the Team

You'll join the fullstack and WMS integration teams at a pivotal moment: live systems, real enterprise customers, and a platform being deliberately re-engineered from growth-era tradeoffs into a durable, enterprise-grade foundation. The team owns everything from customer-facing integrations to the core services and data layer beneath them, and works in close partnership with product, security, and customer success to turn ambiguous requirements into dependable, well-architected systems.

About the Role

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.

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

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

About Gather AI

Gather AI is an artificial intelligence company that provides a platform for retailers to optimize their inventory management. The platform uses machine learning algorithms to analyze data from various sources, including sales data, inventory data, and customer behavior, to provide insights into inventory levels and demand forecasting. The company was founded in 2018 and is headquartered in Vancouver, Canada.
Learn more about Gather AI
Size
10 employees
Industry

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