Technical Lead - AI/ML

ABOUT KAYA

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.

THE OPPORTUNITY

We are seeking a Tech Lead with expertise in AI/ML and full-stack development to drive the development of core platform features. This role is instrumental in architecting and optimizing high-performance AI-driven applications, building robust microservices, and ensuring seamless integration across AI, backend, and frontend systems.

You will lead the development of workflow automation modules, AI-powered search engines, and scalable platforms.

WHAT YOU WILL DO

Develop & Optimize Core AI/ML Features

• Architect and implement AI-powered automation modules, search systems, and data retrieval models.
• Deploy LLM-driven applications using LangChain, RAG, and embedding-based techniques.
• Enhance workflow automation using Haystack, LangGraph, and vector databases.
• Design and build MCP (Model Context Protocol) servers and clients to connect LLM agents with enterprise tools, APIs, and data sources.

Lead Full-Stack Platform Development

• Design and build scalable microservices and event-driven architecture.
• Implement high-performance backend systems in Python, Java, and Node.js.
• Develop AI-integrated dashboards and frontend applications using React.js, Angular, and TypeScript.

AI Model Deployment & DevOps

• Deploy and monitor AI models on Kubernetes, OpenShift, and cloud platforms.
• Implement CI/CD pipelines, containerization, and scalable deployment strategies.

Technical Leadership & Best Practices

• Lead and mentor junior developers and AI engineers.
• Enforce best practices in software engineering, AI model deployment, and full-stack architecture.
• Drive innovation in AI-based workflow automation and platform scalability.

EXPERIENCE AND BACKGROUND

Qualifications

• Bachelors or masters degree in Computer Science, AI, Machine Learning, or a related field.
• 7+ years of experience in AI/ML and full-stack development.
• AI application expertise building AI-powered applications leveraging LLMs, NLP, deep learning models, and agentic frameworks (MCP, tool/function calling).
• Strong programming skills in Python, Node.js, and TypeScript.
• Cloud AI — deep understanding of cloud-based AI solutions (AWS, GCP, Azure).
• APIs and services — experience in microservices, REST/WebSockets, and real-time API development.
• DevOps and MLOps — strong knowledge of DevOps, MLOps, Kubernetes, and CI/CD pipelines.
• Retrieval — experience in vector databases, RAG-based search, and AI-powered data retrieval.

SKILLS

Must-Have Skills

• Expertise in GenAI development and Large Language Models (LLMs).
• Proficiency in LangChain, Haystack, LangGraph, and Model Context Protocol (MCP) for AI-driven workflow automation and agentic tool integration.
• Strong understanding of Natural Language Processing (NLP) and semantic search optimization.
• Experience in vector databases (Pinecone, Milvus, Neo4j) and graph-based AI solutions.
• Hands-on experience with Speech-to-Text technologies (Whisper, Google Text-to-Speech).
• Backend expertise in Java, Python, Node.js, and Spring Boot.
• Frontend skills with React.js, Angular, and TypeScript.
• Proficiency in microservices architecture and API development…