Senior Voice AI Engineer

Role Overview

We are hiring a Senior Voice AI Engineer for Aivar's Delivery organization to take voice AI use cases from discovery through live production for our enterprise customers. You will build and customize voice agents on top of Convogent — Aivar's voice AI accelerator — working directly within customer engagements, delivery timelines, and SOW commitments. This is a hands-on engineering role embedded in customer-facing delivery pods, partnering closely with Delivery Managers, Solution Architects, and customer technical stakeholders to ship measurable outcomes on live calls.

What You'll Do

• 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.

What You'll Bring

• 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.

Preferred Experience

• 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.