Senior Staff Machine Learning Engineer- Voice AI

What you get to do in this role:

The Advanced Technology Group (ATG) at ServiceNow is a customer-focused innovation group building intelligent software and smart user experiences using existing and latest advanced technologies to enable end-to-end, industry-leading work experiences for customers. We are a group of researchers, applied scientists, engineers, and product managers with a dual mission. We build and evolve the AI platform, and partner with teams to build products and end-to-end AI-powered work experiences. In equal measure, we lay the foundations, research, experiment, and de-risk AI technologies that unlock new work experiences in the future.

You will play a major part in building AI and Machine Learning (ML) solutions that transform the user experience and workflow efficiency of enterprise services. Traditional analytical tools tend to require a technically knowledgeable user to produce even simple results. We are taking a completely fresh approach with the expectation that any user, regardless of technical knowledge, can use the AI/ML solutions we develop to operate the services in the enterprise setting in a thoughtful and scalable manner. We are just getting started with our early-adopter customers and we need your help in building and making available an amazing range of solutions to our 5k+ enterprise customers around the world.

• Lead the architecture and technical direction of the core Voice Platform (Audio Acquisition, Conversation Management, Speech Generation, integration with API and self-hosted Voice AI models, Voice Harness)
• Design and drive large-scale, complex agentic systems, including agent orchestration, routing, tool calling and multi-agent workflows, with strict latency and reliability targets
• Partner with product managers, customers and senior leadership to shape the platform roadmap around real use cases and technology challenges
• Own the design and delivery of Voice distributed systems at scale, spanning multiple regions and data centers
• Set engineering standards for architecture, code quality and processes (design reviews, code reviews, testing) across teams
• Drive the evolution of the SRE practice by turning operational learnings into platform capabilities and tooling
• Mentor Staff and Senior engineers, grow technical leaders, and promote knowledge-sharing across Voice AI engineering disciplines Qualifications

To be successful in this role you have:

• Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AIs potential impact on the function or industry.
• 12+ years of relevant industry experience, including technical leadership of large, cross-team initiatives
• A proven track record of architecting and shipping distributed Voice AI or voice platform systems (real-time audio, STT/TTS, telephony or WebRTC) at large operational scale
• 5+ years designing and leading large-scale, complex agentic systems in production (agent orchestration, tool calling, multi-agent coordination)
• 6+ years of development experience with Python, Golang, Java or similar languages
• 3+ years building LLM-based applications (integrating models, not training), including experience with self-hosted model deployment
• Deep experience operating highly available distributed workloads on Kubernetes following a DevOps approach
• Ability to influence architecture and engineering direction across multiple teams and stakeholders
• Experience building software for compliance and security in regulated environments is considered an asset
• Critical thinking about AI integrations for work processes, decision-making or problem-solving. This may include using AI-powered tools, automating workflows, analysing AI-driven insights, or exploring AIs potential impact on the function or industry.
• Experience building with AI tools such as Claude Code, Cursor and Windsurf