Technical Architect - AI

Kaya is an Enterprise AI Execution Platform company helping organizations turn AI into reliable, production-scale business execution.

The platform enables enterprises to redesign and operate business-critical processes using AI, with the governance, control, visibility, and consistency required for real-world enterprise environments. Rather than limiting AI to pilots, assistants, or isolated tasks, Kaya helps organizations put AI to work across end-to-end processes and translate it into measurable business outcomes.

Kaya works across the systems enterprises already rely on, including CRM, ERP, data platforms, AI models, and existing workflows. It provides a unified execution layer for bringing AI into the way work actually gets done, while giving enterprises the ability to understand, govern, and continuously improve how those processes operate.

Kaya is founder-led, venture-backed, and entering a defining stage of growth. The platform is already proven in production with enterprise customers and delivering measurable business value. We are now building the team that will help scale Kaya across the U.S. and North America and establish the Enterprise AI Execution Platform as a new category in enterprise software.

We are looking for an experienced Technical Architect to own and lead the architecture, design, and end-to-end technical solutions of our cutting-edge AI Multi-Agent workflow orchestration and domain solutions platform. You will play a critical role in architecting and implementing innovative solutions leveraging Generative AI, Multi-Agent Systems, LLMs, SLMs, RAG, Knowledge Graphs, MCP, and advanced AI workflows.

As an architect in our fast-paced startup, you’ll directly code, mentor, grow the engineering team, and ensure alignment of development practices with industry standards, best practices, and architectural vision.

• Lead the end-to-end architecture and design of scalable, secure, and robust GenAI solutions built around Multi-Agent Systems, Generative AI, RAG, Knowledge Graphs, and SLM/LLM integrations.
• Develop detailed solution blueprints, patterns, and architectural standards for multi-agent orchestration and workflow automation.

• Actively participate in coding, prototyping, and hands-on development, particularly in early stages of product and feature development.
• Contribute directly to critical components involving Lang Chain, Lang Graph, Hugging Face, vector databases, AI-powered agents, and various AI/ML tools.
• Lead implementation of sophisticated data pipelines and integrations with various AI technologies including Voice Agents, Speech-to-Text, Text-to-Speech, and Realtime Speech-to-Speech solutions.

• Mentor, groom, and expand technical leads and engineers, fostering innovation, autonomy, and accountability.
• Ensure technical teams adhere to the defined architectural standards, AI solutioning best practices, and technical roadmaps.

• Collaborate with Product, Delivery, and client-facing teams to translate business objectives into technical deliverables.
• Clearly communicate architectural strategies, trade-offs, and technical decisions to both technical and non-technical stakeholders.

• Drive adoption of best practices in software and AI architecture, scalability, maintainability, and performance optimization.
• Ensure alignment with Responsible AI guidelines and regulatory standards.

• 12+ years of hands‑on experience in Software Development and Solution Architecture, including significant experience architecting AI‑powered solutions.
• Bachelor’s or master’s degree in Computer Science, AI, Engineering, or related technical fields.
• Enterprise‑scale AI delivery — background in building AI solutions for enterprise‑scale use cases with demanding real‑time or high‑performance requirements.
• Startup track record — working effectively in a fast‑paced, agile, startup environment.
• Deep hands‑on experience with: Generative AI & Multi‑Agent Systems, AI Integration & Workflows, and Data Pipelines & AI Integrations.
• Excellent communicator and team leader — capable of clearly explaining complex technical concepts across diverse audiences, with proven ability to lead and mentor technical teams, particularly in dynamic startup settings.