Full Stack Software Engineer, Atlas Applications

Responsibilities

• Work directly on Atlas' agentic capabilities, utilizing VLMs, tool calls, context engineering, and memory to build a flexible and performant task execution system.
• Develop the operator dashboards, task configuration UIs, and diagnostic interfaces to help users build and deploy Atlas applications.
• Design and implement observability frameworks, structured logging, and tracing infrastructure to provide visibility into system behavior and performance.
• Develop and utilize evaluation and benchmarks to measure reasoning quality, safety, reliability, and generalization across tasks and environments.
• Collaborate cross-functionally with agentic systems, behavior, controls, perception, and product experts to ship end-to-end capabilities.
• Engage with customers and internal stakeholders to understand real-world use cases and ensure solutions are practical, reliable, and impactful.
• Contribute to a strong engineering culture through code reviews, testing, documentation, and thoughtful system design.

Requirements

• 3+ years of professional software engineering experience with a strong full stack background spanning frontend, backend, and LLM integrations.
• Demonstrated ability to design and integrate APIs and third-party services in complex, multi-system environments.
• Strong fundamentals in data structures, algorithms, distributed systems, and software architecture.
• Proficiency in modern frontend frameworks (e.g., React), backend technologies (e.g., Python, TypeScript) and databases (e.g. Postgres, Redis, Pinecone).
• Demonstrated ability to ship reliable, maintainable, and well-tested software while utilizing agentic coding tools like Claude Code.
• Comfort working in fast-moving, ambiguous environments where you're expected to own problems end to end.

Preferred Experience

• With LLM products and/or agentic systems, including prompt engineering, context window management, or tool-use orchestration (e.g. coding agents).
• Experience working with robotics systems, vision models, or real-time data pipelines.
• Strong proficiency in TypeScript and/or Python with comfort operating across large codebases.
• Familiarity with observability platforms (e.g. OpenTelemetry) and evaluation frameworks for AI systems.