Staff Machine Learning Engineer, Agentic AI Harness & Quality - Moveworks

The Role

We are looking for an experienced software engineer with machine learning expertise to join us in expanding Moveworks agentic AI capabilities, enabling increasingly magical user experiences and improving Moveworks agentic and conversational AI capabilities platform-wide.

As a member of the Agentic AI Harness & Quality team, you will have all the tools of modern agentic AI engineering at your disposal, from best-in-class LLMs, multimodal foundation models, and hybrid vector databases to all the infrastructure needed to tune, evaluate, and serve both models and agents in production. We are an eval-driven, data-centric team, and you will have the assistance of a world-class annotation team to build error-free, inclusive, and privacy-preserving datasets for tuning and evaluation. 

You will also go beyond model training to achieve state-of-the-art AI performance in production, in every meaning of the word “performance”: not just accuracy and quality of outputs, but also latency, reliability, and capability of the end-to-end user-facing system as a whole. Successful machine learning engineers on the team are motivated to design and maintain high-performing compound AI systems, with model training as one tool among many in the toolbox rather than the central responsibility of the job.

Our team indexes on increasing our ability to move fast, solving challenging product and engineering challenges, and pushing the envelope of agent reliability and value provided to customers. Your work will impact our team’s core objective to build the highest-performing enterprise assistant platform the world has ever seen, in close collaboration with other functions within Moveworks and ServiceNow as a whole.

What you get to do in this role:

• Apply software engineering, machine learning, and compound AI system engineering to create lasting value for all our customers

• Drive quality in agent behavior, both in terms of increasing utility for end users and decreasing misbehavior in the customer business environment

• Take on exciting and difficult challenges in AI harness engineering, such as agent cognitive architecture, eval benchmark creation, context engineering, generative UI, dynamic agent orchestration, multimodal I/O, multilinguality, conversational memory management, reasoning strategies, abstractive summarization, grounding and verifiability for generated text, deployment safety, and self-learning

• Read, discuss, and build on the latest ML/LLM research and open-source repositories and models

• Research and develop innovative, scalable and dynamic solutions to hard problems

• Use your knowledge of machine learning fundamentals and LLMs to make improvements to the agentic harness and its AI components, evaluate them with small scale experiments and productionize your solutions at scale

• Partner closely with web and chat platform engineering teams to turn harness investments into delightful user experiences that wow our customers

Function: Engineering
Experience Level: Not Applicable