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ServiceNow is building a real-time conversational AI voice platform that orchestrates every call through Voice Activity Detection, Speech-to-Text, LLM-based agent matching, tool calling against ServiceNow APIs, and Text-to-Speech. In voice systems, latency and reliability are the product itself.
As a Staff SRE Engineer on the Voice Core Platform, you will own the platform's reliability, performance, and operational architecture, setting direction across teams. Your responsibilities include:
• Define and drive SLIs/SLOs for availability, perceived latency (end-of-speech to first audio), and call quality metrics.
• Instrument end-to-end distributed tracing across every pipeline stage and lead architectural work to cut latency.
• Design autoscaling and capacity planning for stateful, real-time connections (WebSocket, WebRTC, SIP/RTP).
• Lead load, soak, and breakpoint testing, converting results into capacity models.
• Build resilience patterns for LLM, STT, and TTS dependencies: failover strategies, fallbacks, rate-limit handling, and graceful degradation.
• Own Kubernetes architecture, infrastructure-as-code, and CI/CD with safe progressive delivery practices.
• Lead incident response and postmortems; mentor engineers across the team.
This is a high-impact role at the intersection of AI orchestration and production reliability, requiring deep expertise in real-time systems and modern cloud infrastructure.
REQUIREMENTS:
• 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 IaC tools.
• Hands-on observability experience (OpenTelemetry, Prometheus, Grafana, Datadog, or similar).
• Proficiency in Python, Go, or Java.
• Experience with AI integration into work processes, decision-making, or problem-solving.
NICE TO HAVE:
• Inference serving experience (vLLM, Triton, GPU scheduling).
• Familiarity with the ServiceNow platform or enterprise SaaS backends.
