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Pendo is building the next generation of product analytics focused on agentic systems. This Full Stack Software Engineer role sits on a team that helps companies understand how their AI agents behave in production—what tools get called, where failures occur, and what needs fixing.
You will own features end-to-end across Go backend services, Vue frontend interfaces, installation experiences, instrumentation, telemetry, and LLM-backed product capabilities. Day-to-day work includes shipping full-stack features with production reliability, building lightweight install and instrumentation experiences that customers embed in their own agentic systems, capturing and visualizing agent behavior (tool calls, failures, latency, contract mismatches), developing LLM-backed features including prompt design and tool calling, and shipping incrementally behind feature flags with appropriate test coverage.
The role emphasizes production ownership—you write code others can operate, monitor what you ship, and drive follow-up work to reduce recurrence. You'll collaborate with a team that values clear communication, useful code reviews, and documentation that outlasts your involvement.
Pendo values builders over maintainers: engineers who thrive when there's no clear path, identify gaps, shape solutions, and operate as strategic advisors. The team is deeply AI-curious—not using AI tools occasionally, but rewiring workflows around them as a multiplier for speed, quality, and judgment.
Required: 3+ years shipping full-stack SaaS features to production; strong backend (Go, Java, Python, C++) and frontend (Vue, React, Angular) skills; API design and AWS/GCP service experience with SQL databases; hands-on LLM building (API integration, prompt/context design, tool calling); agent framework experience (LangChain, LangGraph); testing discipline (unit, integration, E2E) with safe rollout patterns; ability to take well-scoped problems to production independently; active AI tool use in development; strong written communication; BS in Computer Science or equivalent.
Nice-to-haves: MCP server or agent tooling experience; SDK or instrumentation library shipping experience.
