Job Description

About the role

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 platforms reliability, performance and operational architecture, and set direction across teams.

What youll 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 protected progressive delivery.
- Lead incident response and postmortems, and mentor engineers across the team. 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 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.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Staff SRE Engineer - Voice Core Platform (Ahmedabad)
🏢 armis
📍 Ahmedabad