{"id":3603684,"url":"https://alion.io/job/moveworks-staff-sre-engineer-voice-core-platform","title":"Staff SRE Engineer - voice Core Platform","company":{"id":840,"name":"Moveworks","domain":"moveworks.com","url":"https://alion.io/company/moveworks","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Datadog","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Glide","optional":false},{"name":"Grafana","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Progressive Delivery","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"ServiceNow","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"Terraform","optional":false},{"name":"Text-to-Speech","optional":false},{"name":"WebRTC","optional":false},{"name":"WebSockets","optional":false},{"name":"Kotlin","optional":true},{"name":"Triton","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-11-02T10:35:10Z","employer_posted_date":null,"last_verified_at":"2026-11-02T10:35:10Z","board_verified":false,"closed_at":null,"days_open":3,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":3},"description":"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.\n\nResponsibilities: \nDefine and drive SLIs/SLOs for availability, perceived latency (end-of-speech to first audio), and call quality.\nInstrument end-to-end tracing across every pipeline stage, and lead architectural work to cut latency.\nDesign autoscaling and capacity plans for stateful, real-time connections (WebSocket, WebRTC, SIP/RTP).\nLead load, soak and breakpoint testing, and turn results into capacity models.\nBuild resilience for LLM, STT and TTS dependencies: failover, fallbacks, rate-limit handling and graceful degradation.\nOwn Kubernetes architecture, infrastructure-as-code and CI/CD with safe progressive delivery.\nLead incident response and postmortems, and mentor engineers across the team.\n\nRequirements: \nExperience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving.\nThis may include using AI-powered tools, automating workflows, analysing AI-driven insights, or exploring AI's potential impact on the function or industry.\n8+ years in SRE, DevOps, production engineering or software engineering on production systems at scale.\n1+ year building or operating real-time voice systems (VoIP, SIP/RTP, WebRTC, or STT/TTS integration).\n2+ years building or operating AI agentic systems and orchestration pipelines (agent routing, tool calling, multi-step LLM workflows).\n1+ year deploying and operating LLMs in production (model serving, inference optimisation, provider integration and failover).\nStrong expertise in Kubernetes, cloud infrastructure ([AWS / Azure / GCP]) and Terraform or similar.\nHands-on observability experience (OpenTelemetry, Prometheus, Grafana, Datadog or similar).\nProficiency in Python, Go or Java.\n\nNice to have: \nExperience in inference serving (vLLM, Triton, GPU scheduling).\nFamiliarity with the ServiceNow platform or enterprise SaaS 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