Aivar Innovations is an AI-native services and software company and AWS Preferred Partner, backed by Bessemer Venture Partners and Sorin Investments. Founded by four former Amazon Web Services senior leaders, Aivar operates three accelerator platforms — Convogent (voice and agent AI automation), Velogent (governed agentic process automation for regulated industries), and Kubogent (Kubernetes-native AIOps) — serving enterprises across fintech, healthcare, and technology verticals. With a studio-built approach and deep AWS expertise, Aivar delivers production-grade AI solutions at enterprise scale.
The Conversation AI Architect is a senior technical leader within Aivar's Engineering and Solution Architecture team. In this role, you will be the primary technical authority for designing and delivering enterprise-grade conversational AI solutions, primarily anchored on the Convogent accelerator platform.
You will partner closely with enterprise clients across fintech, healthcare, and technology sectors, leading solution design from discovery through production. You will shape the evolution of Convogent's architecture, define best practices for agentic AI deployments, and work in close collaboration with the Velogent team to embed governance and compliance into conversational workflows.
This is a high-impact, client-facing role at the intersection of AI architecture, solution engineering, and technical leadership. You will operate as a trusted advisor to clients, a thought leader within Aivar, and a hands-on architect who can move between whiteboard and codebase with equal confidence.
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Architect end-to-end conversational AI solutions leveraging the Convogent platform, AWS Bedrock, Amazon Lex, Amazon Connect, and related services.
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Design multi-turn dialogue systems, intent classification frameworks, and entity extraction pipelines for enterprise-scale deployments.
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Define agentic AI orchestration patterns, including ReAct-style agents, tool-using LLM workflows, and multi-agent coordination architectures.
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Develop reference architectures for voice AI, chat automation, and hybrid human-agent escalation systems.
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Ensure solutions are secure, scalable, observable, and aligned with enterprise governance standards — particularly for regulated industries served via Velogent.
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Lead technical discovery workshops with enterprise clients to understand conversational workflows, pain points, and automation opportunities.
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Own the pre-sales technical engagement: scope solutions, produce architecture proposals, and present to technical and executive stakeholders.
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Serve as the primary technical point of contact throughout project delivery, from design through go-live and post-launch optimization.
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Guide client teams on conversational AI best practices, LLM prompting strategies, and responsible AI deployment.
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Contribute to the Convogent platform roadmap by identifying capability gaps and leading the design of new features and integration patterns.
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Build and maintain accelerator components, reusable dialogue templates, and integration blueprints that reduce time-to-deploy for future engagements.
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Work with the Velogent team to embed agentic governance controls — audit trails, escalation policies, compliance guardrails — into conversational AI workflows.
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Evaluate emerging LLM capabilities (Amazon Bedrock model updates, Claude model releases, new foundation models) and assess their applicability to Aivar's accelerator platforms.
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Write and review production-quality Python and Node.js code for backend AI services, orchestration layers, and AWS Lambda functions.
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Define and enforce quality standards for conversational AI: intent accuracy benchmarks, latency SLAs, fallback handling, and A/B testing frameworks.
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Implement observability and feedback loops for deployed agents — monitoring conversation quality, intent coverage, and escalation rates in real time.
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Mentor junior engineers and solution architects; run internal knowledge-sharing sessions on conversational AI and agentic architecture patterns.
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8+ years of overall experience in software engineering, AI/ML, or solution architecture.
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5+ years of hands-on experience designing and deploying conversational AI systems in production environments.
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Proven track record of leading enterprise AI engagements from architecture through delivery.
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Experience working with large language models (LLMs) in production, including prompt engineering, fine-tuning evaluation, and model evaluation.
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AWS Certified Solutions Architect (Professional) or AWS Certified Machine Learning Specialty.
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Experience with Amazon Connect CCP, Contact Flows, and contact center AI transformations at scale.
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Contributions to open-source conversational AI or agentic AI projects.
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Prior experience in a consulting, professional services, or startup environment delivering multiple concurrent client engagements.
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Exposure to MLOps practices: model versioning, CI/CD pipelines for AI systems, shadow deployment, and canary rollouts.
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Experience with multimodal AI systems combining voice, text, and structured data inputs.
