What we do
Augmentus is a leading provider of robotic programming solutions that simplify and streamline traditionally complex industrial automation processes. Our innovative solution integrates cutting-edge features like 3D scanning, automated path optimization, and seamless robot code generation to make programming accessible and efficient for manufacturers handling high-mix, high-part complexity operations. Trusted by global leaders in industries such as media blasting, painting, and welding, Augmentus empowers companies to achieve scalability, reliability, and superior operational efficiency. Join us to revolutionize the future of robotics and automation.
About your role
You’ll join a small, fast-moving AI team building production systems that combine software engineering with AI capabilities. This is a hands-on engineering role — you’ll work on real features, ship real code, and learn by doing.
What You’ll Work On
– Build and maintain Python services and APIs that support the agent system and its automation workflows
– Assist in developing and testing agent capabilities — tool integrations, data pipelines, multi-step workflows
– Develop and improve evaluation, metrics, guardrails for autonomous agents
– Write clean, well-tested code with proper error handling, logging, and documentation
– Integrate various data sources, services, and APIs into the agent’s execution environment
– Contribute to CI/CD pipelines, testing infrastructure, and developer tooling
– Debug, investigate, and fix issues across the stack — independently where possible
– Pick up new tools, frameworks, and domains quickly as the team’s needs evolve
What We’re Looking For
– Solid CS fundamentals — data structures, algorithms, systems thinking. You can reason through problems and write clean solutions.
– Strong Python proficiency. JavaScript/TypeScript is a plus.
– Self-driven problem solver — you don’t wait to be told the next step. You dig in, read docs, try things, and ask good questions when you’re stuck.
– Good engineering habits — version control, testing, code review, structured debugging.
– Familiarity with APIs, backend concepts, and working in a terminal/CLI environment.
– Curiosity about AI/ML — you don’t need deep experience, but you should have some intuition for how LLMs work and a genuine interest in building with them.
Nice to Have
– Hands-on experience with LLMs (prompt engineering, tool calling, structured outputs, RAG).
– Exposure to ML concepts (training, evaluation, embeddings, basic model architectures).
– Familiarity with computer vision concepts (detection, segmentation, classification).
– Experience with cloud platforms (GCP, AWS).
– Experience with robotics or industrial automation domains.
– Comfort with AI-assisted development tools (e.g. Claude Code, AI code assistants).
