Technical Architect - AI

Kaya is an Enterprise AI Execution Platform companyhelping organizations turn AI into reliable, production-scale businessexecution.

The platform enables enterprises to redesign and operatebusiness-critical processes using AI, with the governance, control, visibility,and consistency required for real-world enterprise environments. Rather thanlimiting AI to pilots, assistants, or isolated tasks, Kaya helps organizationsput AI to work across end-to-end processes and translate it into measurablebusiness outcomes.

Kaya works across the systems enterprises already relyon, including CRM, ERP, data platforms, AI models, and existing workflows. Itprovides a unified execution layer for bringing AI into the way work actuallygets done, while giving enterprises the ability to understand, govern, andcontinuously improve how those processes operate.

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

We are looking for an experienced Technical Architect toown and lead the architecture, design, and end-to-end technical solutions ofour cutting-edge AI Multi-Agent workflow orchestration and domain solutionsplatform. You will play a critical role in architecting and implementinginnovative 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’lldirectly code, mentor, grow the engineering team, and ensure alignment ofdevelopment practices with industry standards, best practices, andarchitectural vision.

TechnicalArchitecture Ownership

•       Lead the end-to-endarchitecture and design of scalable, secure, and robust GenAI solutions builtaround Multi-Agent Systems, Generative AI, RAG, Knowledge Graphs, and SLM/LLMintegrations.

•       Develop detailed solutionblueprints, patterns, and architectural standards for multi-agent orchestrationand workflow automation.

Hands-on EngineeringLeadership

•       Actively participate in coding,prototyping, and hands-on development, particularly in early stages of productand feature development.

•       Contribute directly to criticalcomponents involving LangChain, LangGraph, Hugging Face, vector databases,AI-powered agents, and various AI/ML tools.

•       Lead implementation ofsophisticated data pipelines and integrations with various AI technologiesincluding Voice Agents, Speech-to-Text, Text-to-Speech, and RealtimeSpeech-to-Speech solutions.

Team Development& Technical Mentorship

•       Mentor, groom, and expandtechnical leads and engineers, fostering innovation, autonomy, andaccountability.

•       Ensure technical teams adhereto the defined architectural standards, AI solutioning best practices, andtechnical roadmaps.

StakeholderEngagement & Cross-Team Collaboration

•       Collaborate with Product,Delivery, and client-facing teams to translate business objectives intotechnical deliverables.

•       Clearly communicatearchitectural strategies, trade-offs, and technical decisions to both technicaland non-technical stakeholders.

Best Practices &Standards Enforcement

•       Drive adoption of bestpractices in software and AI architecture, scalability, maintainability, andperformance optimization.

•       Ensure alignment withResponsible AI guidelines and regulatory standards.

Requirements

RequiredQualifications

•       12+ years of hands-onexperience in Software Development and SolutionArchitecture, including significant experience architecting AI-poweredsolutions.

•       Bachelor’s or master’sdegree in Computer Science, AI, Engineering, orrelated technical fields.

•       Enterprise-scale AI delivery— background in building AI solutions forenterprise-scale use cases with demanding real-time or high-performancerequirements.

•       Startup track record — working effectively in a fast-paced, agile, startup environment.

•       Deep hands-on experiencewith: Generative AI & Multi-Agent Systems, AIIntegration & Workflows, and Data Pipelines & AI Integrations.

•       Excellent communicator andteam leader — capable of clearly explaining complextechnical concepts across diverse audiences, with proven ability to lead andmentor technical teams, particularly in dynamic startup settings.