About Gnani.ai-
Gnani.ai is a frontier Voice AI company, building best-in-class AI models and agentic AI platforms that solve problems at scale. Our proprietary stack — speech recognition, text-to-speech, small language models, and agentic voice platforms across 40+ languages — powers real-time conversations in production for some of the most demanding enterprises in the world.
We own our stack end to end. That is our moat — and product is how we turn that depth into experiences customers and developers love.
The Role
We are hiring a VP of Engineering to lead the organization that builds and runs our voice platform — the real-time runtime, the product surfaces on top of it, and the cloud and telephony infrastructure that keep it fast and reliable under enterprise load.This is a senior, deeply technical leadership role reporting to the Chief Product & Engineering Officer.
You will set engineering strategy, scale a multi-team organization, and stay close enough to the system to own the hard calls on architecture, latency, and reliability yourself. Our AI research organization owns the models; a separate Delivery organization owns customer implementations. Your mandate is to make the platform something both of them can build on with total confidence.
What You'll Own
- The real-time voice platform & runtime — the orchestration layer where telephony, speech, and agentic logic meet, engineered for low latency and high concurrency.
- Product engineering — the teams building our agentic voice platform, our voice and speech products, and a growing speech-analytics product.
- Infrastructure, DevOps & telephony — Kubernetes-based cloud infrastructure, the VoIP/telephony stack, observability, release engineering, and security operations.
- Reliability & scale — SLAs, on-call, incident response, capacity and concurrency provisioning, and cost-efficient operation at the platform layer.
- Quality & test engineering — test strategy, test automation, and release quality across the product pods, with QA embedded close to the teams it serves.
- The engineering organization — hiring, structure, manager development, the technical bar, and engineering culture, partnering with a Principal Architect who holds cross-product technical authority.
What We're Looking For
You are a sitting engineering leader at an enterprise SaaS or high-growth product company, and you have built and scaled engineering organizations that ship demanding software in production.
Core — what matters most
- 15+ years in software engineering, with several years leading at Director / Sr. Director / VP level at a product company.
- Has personally architected and scaled distributed, low-latency or real-time systems in production— and can still go deep with the strongest engineers.
- A track record of scaling an engineering org through growth: hiring senior talent, managing managers and technical leaders, and raising the bar without slowing delivery.
- Strong cloud-native and reliability depth — Kubernetes, observability, on-call/incident discipline, capacity and cost management at scale.
- Enterprise-grade instincts — multi-tenancy, security, and operating under real customer SLAs and compliance obligations.
- Partners cleanly with peer AI and Product leaders, keeping ownership boundaries crisp.
Strong advantage — what sets a candidate apart-
- Building or operating GenAI / agentic-AI platforms comparable to ours.
- Real-time communications, streaming, media, or voice — SIP/RTP, telephony, VAD, ASR/TTS orchestration.
- Running LLM / agentic systems in production.
- Familiarity with the Indian enterprise market and its regulatory environment (DPDP, RBI, IRDAI,TRAI, and HIPAA-type regimes).
- Exposure to multilingual / Indic products.
A note on the bar: deep voice-AI or model-research experience is a plus, not a prerequisite. We are looking first for an exceptional, scaled, hands-on engineering leader.
Skills & Competencies
- Hands-on engineering — still writes and reviews production code; fluent in one or more modern backend languages (e.g. Go, Python, Rust, Java) and sets the bar by example.
- System architecture & design — strong command of design principles, patterns, and trade-off analysis; clean service boundaries and well-considered APIs (REST / gRPC / streaming).
- Distributed systems at scale — designing and operating low-latency, high-concurrency backend services.
- Event-driven & streaming architectures — message buses and pub/sub (e.g. Kafka, NATS), async and stream processing, queueing, and backpressure.
- SQL & NoSQL databases — sound data-modelling judgement, choosing the right store, and tuning for scale; plus caching and in-memory stores (e.g. Redis).
- Cloud-native engineering — Kubernetes, containers, microservices, and infrastructure-as-code.
- Reliability engineering — SLAs / SLOs, observability, on-call and incident management, capacity and cost planning.
- Performance & efficiency — profiling and optimising latency and cost at the platform and serving layers.
- Enterprise-grade software — security, multi-tenancy, and data protection by design.
- Advantageous — real-time media and telephony (SIP / RTP / WebRTC, VAD, ASR/TTS orchestration), and serving LLM / agentic systems in production.
Leadership & operating
- Scaling organisations — building and structuring multi-team engineering groups through growth.
- Talent — hiring senior engineers and developing engineering managers.
- Leading leaders — has directly managed technical leadership — Architects, Engineering Managers, and QA leads — not only individual contributors.
- Technical bar & governance — setting standards, owning architecture decisions, and making the hard calls.
- Cross-functional partnership — working cleanly with AI, Product, and Delivery leaders.
- Strategy to delivery — translating business goals into engineering roadmaps and predictable execution.
Why This Role
The platform is real, in production, and growing — this is a scaling challenge, not a greenfield bet. You
will inherit a capable team and a clear mandate, with the CPEO sponsoring the function directly
through your onboarding. If you want to own the engineering of a category-defining, India-first voice-AI
platform and build the organization that scales it, this is the seat.
