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Aivar Innovations

<div><div><b>Senior Voice AI Engineer</b></div><div><b>
Platform:</b> Convogent</div><div>
<b>Level:</b> Mid&ndash;Senior (5+ years | 2+ years building voice AI in production)</div><div>
<b>Location:</b> Bangalore Office</div><div><b>
About the Role</b></div><div>
You will own the <b>distributed, real-time systems that orchestrate parallel voice calls at massive scale</b>: the core platform behind every conversation Convogent runs. The job is keeping thousands of simultaneous calls fast, reliable, and natural, owning how STT/ASR, LLM, TTS, RAG, and tool-calling work together, and where every millisecond and every point of quality goes across the pipeline.</div><div></div><div><b><br>
What you&rsquo;ll do</b></div><ul><li><b>
Own voice AI at scale.</b> Keep the pipeline fast and reliable at enterprise concurrency, thousands of simultaneous calls, by lifting calls-per-vCPU through extending Pipecat or rewriting hot paths in Go.</li><li><b>
Own end-to-end latency.</b> Keep the conversation under ~800ms by decomposing the budget across STT, LLM, TTS, RAG, tool-calling, turn-detection, and network hops.</li><li><b>
Diagnose the bad call.</b> When a call does not feel right, locate the fault in the pipeline fast by asking the right questions, reading the right signals, and owning the fix.</li><li><b>
Make quality measurable.</b> Build voice-to-voice evals that gate releases and catch STT/LLM/TTS provider drift before customers do.</li><li><b>
Own provider tradeoffs.</b> Decide how STT / LLM / TTS / RAG / tool-calling choices balance voice quality against latency, per conversation flow.</li><li><b>
Build adjacent products.</b> Extend the platform into live assist, agent assist, and what comes next, on the same pipeline foundations.</li><li><b>
Set the bar.</b> Review, mentor, and define engineering standards for a growing team.</li></ul><div></div><div><b><br>
What we&rsquo;re looking for</b></div><ul><li><b>
5+ years building production products and systems</b>, with at least 2 of those years in real-time voice, operating it in production, not just shipping a demo.</li><li><b>
Deep understanding of the full voice pipeline</b>, every stage end to end and how each one affects the next and shapes quality and latency.</li><li><b>
Strong in Go/Python</b>, comfortable across the whole pipeline. Production-grade, performance-critical Go is especially valued: you have rewritten hot-path components in Go to lift throughput under real load.</li><li><b>
A track record of running voice AI at scale</b>, scaling Pipecat (or a comparable real-time voice framework) to high concurrency in production.</li><li><b>
Provider-tradeoff fluency:</b> how STT / LLM / TTS / RAG / tool-calling choices play off each other on quality and latency.</li><li><b>
An eval-driven approach to quality.</b> You measure voice quality with real signals, not vibes, and have built or run evals on a real-time voice or LLM system.</li><li><b>
Fluency with agentic coding tools</b> and a habit of treating quality as a measured signal.</li></ul><div></div><div><b><br>
What we&rsquo;re NOT looking for</b></div><ul><li>
A <b>prompt engineer / &quot;AI app&quot; builder</b> who has only called LLM APIs and never operated a real-time pipeline under load.</li><li>
Someone who has only <b>used</b> managed platforms (Vapi/Retell/Bland) and never scaled the layer beneath them.</li><li>
A pure <b>web-backend CRUD</b> engineer with no real-time/streaming/voice exposure.</li><li>
An <b>ML researcher</b> who wants to train/fine-tune models. We integrate providers; we don't build models.</li></ul></div><div></div>

Senior Voice AI Engineer

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 Forward Deployed Engineers are the technical bridge between Aivar's accelerators and our customers' hardest problems. You will embed with strategic enterprise customers to scope, design, build, and ship Generative AI and agentic systems into production &mdash; and feed everything you learn back into our product roadmap. This is not sales engineering or traditional consulting. You will write code, design systems, and own outcomes end-to-end &mdash; operating with high autonomy and representing Aivar at the most senior levels in customer environments. Think hands-on AI startup CTO inside the customer's organization, with Aivar's accelerators, AWS partnership, and engineering bench behind you.
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 What You'll Do
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  Embed with customers. Work directly with engineering, product, and business teams to understand workflows, data, and the outcomes they need.  Translate ambiguity into design. Decompose business problems into AI and agentic system designs grounded in evals, latency budgets, and cost envelopes.  Own the technical narrative. Run architecture reviews and workshops with C-suite, IT, and security stakeholders.  Architect on AWS. Build production systems on Bedrock, SageMaker, Lambda, and EKS, using Aivar's accelerators as the foundation.  Build agentic systems. Develop LLM workflows &mdash; prompt engineering, RAG, tool use, multiagent orchestration, evaluation harnesses, and guardrails.  Integrate deeply. Connect with customer systems of record &mdash; ERPs, data warehouses, CRMs, contact-center platforms, and legacy APIs.  Ship to production. Take systems from prototype to hardened deployment &mdash; observability, SLOs, cost optimization, security reviews, and runbooks.  Drive adoption. Define success metrics with the customer, instrument systems to measure them, and iterate until the numbers move.  Enable customer teams. Lead change management and training so customers can extend what you build.  Feed the product. Codify repeatable patterns into the accelerator roadmap and partner with Product and Engineering on what becomes platform vs. bespoke.
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 What You'll Bring
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  4+ years of software engineering experience, including 2+ years in customer-facing or production-deployment roles (FDE, Solutions Engineer, Applied AI Engineer, or technical founder).  Strong coding fluency in Python and at least one of TypeScript/JavaScript, Java, or Go. You ship production code.  Hands-on production experience with LLMs &mdash; prompt engineering, RAG, agent design, evaluation frameworks, and scaled deployment.  Working knowledge of AWS for AI workloads &mdash; Bedrock, Lambda, S3, IAM, ECS/EKS, and at least one data service (RDS, DynamoDB, or OpenSearch).  Solid ML foundations &mdash; evaluation methodology, problem decomposition, and reasoning about model behavior in production.  Experience integrating across enterprise systems &mdash; REST/GraphQL, event-driven architectures, and at least one of: ERP, data warehouse, CRM, or contact-center platforms.  Strong written and verbal communication. You move comfortably between a CTO working session and a platform engineering code review.
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 Comfort with ambiguity, ownership of outcomes, and a bias to ship.
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Forward Deployed Engineer-AI/ML

Join Aivar Innovations and explore 2   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

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Senior Voice AI Engineer

Forward Deployed Engineer-AI/ML