Machine Learning Engineer, Agentic Application

ServiceNow•Mountain View, CA

18h•Hybrid

About The Position

This role is with Moveworks, an Agentic AI Assistant platform that empowers the workforce by enabling employees to converse with business systems through natural language to find answers and automate tasks. The platform is powered by advanced LLMs, proprietary models, and a sophisticated Agentic AI platform, transforming how work gets done by allowing AI to take initiative, streamline complex workflows, and continuously learn and adapt. Moveworks is trusted by millions of employees at large companies and has been recognized on various prestigious lists. In December 2025, Moveworks was acquired by ServiceNow, combining ServiceNow’s workflow automation with Moveworks’ Reasoning Engine and natural language capabilities to deliver an AI platform for every person and every workflow. The role is on the Conversation Engine team, focusing on scaling and optimizing the Generative AI product for enterprise users. The team encourages innovative ideas to solve unsolved problems and collaborates closely with machine learning experts and cross-functional teams, leveraging user behavior data for informed decisions. The challenge involves scaling and optimizing the conversation engine to support millions of users across multiple chat channels and use cases, and enhancing the end-to-end product infrastructure with high engineering quality and robustness. This includes constructing extensive product infrastructure with user-friendly interfaces for customizing generative AI models, collecting data and feedback, adapting to diverse enterprise use cases, and delivering domain-specific conversational experiences. It also involves designing scalable API abstractions for the conversation platform supporting popular chat clients and optimizing the dialog engine for real-time multilingual translation with minimal memory footprint, low latency, and a streamlined development process. The role also entails championing best practices for coding, API design, scalability, robustness, and optimization, fostering a culture of excellence, and providing comprehensive insights into the performance of the conversational AI product through robust logging, tracing, debugging tools, and automated metrics. Collaboration with ML engineers, application engineers, product teams, and customer support is key for developing new features and scalability initiatives.

Requirements

A strong foundation in computer science and software engineering, coupled with expertise in building scalable systems.
A deep understanding of clean, modular, and scalable API design.
Ability to champion best coding practices and influence fellow engineers to uphold high standards of code quality and craftsmanship.
Passion for optimizing systems and improving performance.
Well-versed in tracing, logging, and metrics frameworks, and possess a systematic approach to quickly identify and resolve latency bottlenecks, race conditions, and throughput limitations.
Ability to independently research new requirements and develop innovative solutions.
Thrive in an environment of fast-paced coding and execution, embracing rapid iterations to deliver results.
Strong communication skills to effectively articulate rationales and design approaches.
Cross-functional awareness that enables seamless collaboration with various teams.
A bachelor's degree or higher in computer science or a related field.
2+ years of professional development experience, specifically in building systems at scale.

Responsibilities

Scaling and optimizing the conversation engine to support hundreds of millions of users, across multiple chat channels and use cases.
Enhancing the end-to-end product infrastructure with the utmost engineering quality and robustness.
Constructing an extensive product infrastructure, complete with user-friendly interfaces that empower engineers and configurators to effortlessly customize and optimize generative AI models.
Designing scalable API abstractions for our conversation platform, which supports all popular chat clients (for example, MSTeams, Slack, and Web) and offers a neutral API for developing other parts of the engineering system.
Optimizing the dialog engine to accommodate a wide range of conversational features, leveraging private domain knowledge unique to each enterprise customer in the cloud, and enable real-time multilingual translation.
Championing the best practices for coding patterns, API design, scalability, robustness, and optimization.
Fostering a culture of excellence and continuous improvements among fellow engineers.
Providing comprehensive insights and visibility into the performance of our conversational AI product by implementing a robust logging and tracing framework, user-friendly debugging and triaging tools, and automated metrics for efficient monitoring and analysis.
Collaborating closely with ML engineers, application engineers, product teams, and customer support teams to drive the development of new features and scalability initiatives.