Staff SRE Engineer - Voice Core Platform

About the role

It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.

Join us to put AI to work for people.

We are building a real-time conversational AI voice platform. An orchestrator runs every call through Voice Activity Detection, Speech-to-Text, LLM-based agent matching, tool calling against ServiceNow platform (Glide) APIs, and Text-to-Speech.

In voice, latency and reliability are the product. You will own the platform's reliability, performance and operational architecture, and set direction across teams.

What you'll do

• Define and drive SLIs/SLOs for availability, perceived latency (end-of-speech to first audio), and call quality.
• Instrument end-to-end tracing across every pipeline stage, and lead architectural work to cut latency.
• Design autoscaling and capacity plans for stateful, real-time connections (WebSocket, WebRTC, SIP/RTP).
• Lead load, soak and breakpoint testing, and turn results into capacity models.
• Build resilience for LLM, STT and TTS dependencies: failover, fallbacks, rate-limit handling and graceful degradation.
• Own Kubernetes architecture, infrastructure-as-code and CI/CD with safe progressive delivery.
• Lead incident response and postmortems, and mentor engineers across the team.

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 AI’s potential impact on the function or industry.
• 8+ years in SRE, DevOps, production engineering or software engineering on production systems at scale.
• 1+ year building or operating real-time voice systems (VoIP, SIP/RTP, WebRTC, or STT/TTS integration).
• 2+ years building or operating AI agentic systems and orchestration pipelines (agent routing, tool calling, multi-step LLM workflows).
• 1+ year deploying and operating LLMs in production (model serving, inference optimization, provider integration and failover).
• Strong expertise in Kubernetes, cloud infrastructure ([AWS / Azure / GCP]) and Terraform or similar.
• Hands-on observability experience (OpenTelemetry, Prometheus, Grafana, Datadog or similar).
• Proficiency in Python, Go or Java.

​​​​​​​Nice to have

• Experience Inference serving experience (vLLM, Triton, GPU scheduling).
• Familiarity with the ServiceNow platform or enterprise SaaS backends.

Work Personas

We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.

Equal Opportunity Employer

Accommodations

Export Control Regulations

For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.

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