About the role
- Own customer delivery outcomes. Take voice AI use cases from discovery through production go-live within committed timelines, working inside Rocketlane-tracked delivery plans alongside your Delivery Manager.
- Customize and configure Convogent. Adapt Aivar's voice AI accelerator (built on Pipecat, LiveKit) to each customer's telephony stack (Twilio, Exotel, Cisco, Vonage, etc.), API/MCP integrations with customer CRM tools, knowledge base (KB) integrations, compliance constraints, and use-case requirements.
- Engineer real-time audio pipelines for production. Optimize STT and TTS flows for the latency, concurrency, and call quality bar each customer engagement demands.
- Troubleshoot customer production systems. When a live call does not sound right, quickly narrow down where in the pipeline it broke — capture, STT, orchestration, or TTS — by asking the right questions, reading the right signals, and driving the fix through to resolution.
- Build and adapt the orchestration layer. Connect STT, TTS, and LLM agents into resilient, observable workflows with guardrails suited to the customer's risk and compliance profile.
- Translate customer requirements into deployable solutions. Work directly with customer technical stakeholders alongside Aivar's SA and DM to scope, size, and iterate use cases against measurable outcomes — success rate, latency, adoption.
- Report and govern delivery. Contribute to sprint tracking, status reporting, and stakeholder governance for the use cases you own.
- Hands-on experience building and deploying voice agents with Pipecat, LiveKit, or similar frameworks — ideally across multiple distinct production deployments, not a single system.
- Deep expertise in STT (Deepgram, Whisper, AssemblyAI, Google STT, Sarvam) and TTS (ElevenLabs, Cartesia, Amazon Polly).
- Working knowledge of Speech-to-Speech (S2S) services, including Amazon Nova Sonic, and how they change pipeline and orchestration design compared to cascaded STT/LLM/TTS.
- Experience with multi-speaker diarization and conversation segmentation.
- Production fluency in Python plus at least one of Node.js, TypeScript, or Go.
- Practical use of AI/ML libraries (TensorFlow, PyTorch, Scikit-learn) and conversational AI design — prompt engineering and integration with LLMs (GPT-4o, Claude, Bedrock models).
- Cloud deployment experience on AWS (Lambda, EC2, S3, EKS, Polly, Transcribe, Bedrock) with Docker, Kubernetes, and CI/CD.
- Demonstrated ability to work under SOW/contract constraints — scoping, prioritizing, and shipping within a defined timeline and budget across live customer engagements.
- Comfort working across multiple concurrent customer engagements with differing requirements, tech stacks, and stakeholders.
- Prior experience in a customer delivery, consulting, or systems integration role, rather than purely product/platform engineering.
- Exposure to regulated industries (fintech, healthcare, BFSI) and their compliance and security constraints.
- Experience with enterprise stakeholder management — running status calls, translating technical tradeoffs into business language.
- Familiarity with low-code voice platforms alongside custom infrastructure.
- Voice analytics, transcription tooling, and Indian-language STT/TTS models.
- AWS or speech technology certifications.
Why This Role, Why Aivar
- Work that ships to real customers. Every use case you build runs live on enterprise calls, measured by customer outcomes, not demos.
- Own delivery end-to-end. From discovery call to production go-live, you are the engineering owner of the customer's voice AI outcome.
- Build on accelerators that work. Convogent has real production traction — you configure and extend a working platform across diverse customer environments.
- Direct customer exposure. Work face-to-face with enterprise technical stakeholders, not just internal teams.
- Backed and proven. AI-native, AWS Preferred Partner, BVP- and Sorin-backed, with 100+ enterprise customers in the first year.