Full Stack Engineer, AI systems

Role overview Build the product layer that turns AI capabilities into dependable, end-to-end workflows in an agent-first communication application. The work spans frontend, backend, and AI integration, with particular attention to how agents plan tasks, use tools, recover from errors, and provide timely results in real-world conditions.

Responsibilities - Deliver product features across the frontend, backend, and AI integrations, from initial design through production. - Design multi-step agent workflows that support planning, tool use, failure handling, and recovery across tools and sessions. - Integrate language models, memory, and external services into scalable product systems. - Build responsive real-time interactions with streaming and partial results while managing latency. - Improve reliability through observability, evaluation, monitoring, and fallback mechanisms. - Iterate based on actual usage and failure patterns, working closely with machine learning, backend, and product teammates.

Requirements - Strong full-stack engineering experience across frontend and backend development. - Solid understanding of system design and API architecture. - Experience with LLMs, retrieval-augmented generation, or AI-powered applications. - Ability to make pragmatic decisions amid evolving requirements and take features from idea to production. - Comfort working independently in a fast-moving environment.

Nice to have - Familiarity with Next.js, Python, Node.js, PyTorch, SQL or NoSQL databases, Kubernetes, or Docker. - Experience with OpenAI, Anthropic, or open-source language models.

Benefits and work setup The team describes a small, hands-on environment with collective decision-making, rapid iteration, and a balance between shipping and learning. The hiring process typically involves three to four interviews, conducted virtually and/or onsite.