About the job
Are you a software engineer who has honed your craft through internships, research, and/or academic projects, and are looking to apply your skills at the cutting edge of AI agents? This may be the role for you. As a software engineer on our “agent lab” Natural Language Understanding team, you will play an important part in our mission: to advance the frontier of work that can be entrusted to agents to perform reliably at scale. You will have the opportunity to contribute to the evolution of the Moveworks AI Assistant platform in several of the following areas: agent orchestration, sandboxed file systems and code execution, latency optimization, agent memory, LLM self-reflection and improvement, execution environment simulation, enterprise knowledge graphs, and multimodal I/O.
Responsibilities
Take on exciting engineering challenges (see areas listed above) to build and evolve capable AI agent systems that are reliable in every sense of the word
Implement frontier AI algorithms and architectures and help productionize them at scale, with support from senior engineers
Use the latest advances in machine learning, LLMs, and AI agents to enhance our products and create delightful user experiences
Execute on projects to create lasting value for all our customers
Hone your craft in writing robust, extensible, readable, and performant code
Partner with subject matter experts across the company including in machine learning, security, product, user experience, and customer success, to learn from each other and build the best enterprise AI product the world has ever seen
Learn from and collaborate with senior engineers and machine learning engineers to build world-class AI systems
Qualifications
Minimum
Strong programming fundamentals and experience building software through coursework, projects, internships, and/or research
Ability to think and communicate clearly about engineering problems and systems
Eagerness to learn, give and receive feedback, and hold yourself to a high standard of operational excellence
Readiness to hit the ground running in a Mac development environment, programming in Python, Golang, and/or Java
Desire to ship at a startup pace with a high degree of ownership
Attention to detail
Drive to ship product improvements with production-grade code (with guidance and iterative development)
High level of curiosity about engineering outside of immediate discipline and ongoing desire to learn and stay at the cutting edge of applied AI
Preferred
Internship or research experience building production-quality software
Experience building with LLMs, particularly in iterating on prompts, on model selection, on cognitive architecture design, and on latency/correctness tradeoffs in a data-driven way
Hands-on experience with one or more stages of a machine learning problem-solving lifecycle, such as experiment setup, dataset curation, model training, offline evaluation and error analysis, deployment, and online evaluation
Experience in AI fairness, privacy, permission controls, safety, and/or security