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Maisa AI is building an agentic process automation platform that helps enterprises automate complex, decision-heavy workflows that traditional automation and GenAI cannot reliably handle. The platform combines AI-driven problem solving with programmatic execution to deliver reliable, auditable, enterprise-scale automation.
As an Applied AI Engineer on the Research team, you will be a hands-on builder bridging research and production. You'll design and implement end-to-end AI agent workflows using Maisa's proprietary KPU technology, working directly with enterprise customers to rapidly iterate on solutions that solve real business problems.
Key responsibilities include:
- Design and implement production-ready AI agent workflows, collaborating with customers on rapid iteration cycles
- Build robust evaluation datasets and frameworks to measure agent performance, reliability, and accuracy
- Optimize workflows for performance, explainability, and enterprise-grade reliability
- Push boundaries of LLMs, RAG systems, and AI agents in production environments
- Stay current with agentic AI development techniques and continuously improve the platform
You should bring demonstrable experience shipping AI-powered features to production, strong hands-on expertise with LLMs, prompt optimization, and context engineering in real-world applications. A strong software engineering background with Python proficiency for production systems is essential, along with understanding of ML system evaluation methodologies and performance optimization. You'll translate complex AI capabilities into practical enterprise applications, thrive as an individual contributor in fast-paced startup environments, and are passionate about building reliable, transparent, trustworthy AI systems.
Maisa recently closed a $25M Seed Round backed by Creandum, Forgepoint, NFX, and Village Global, and is scaling with significant enterprise traction. You'll work alongside deep technical and industry experts on genuinely differentiated technology solving real enterprise AI challenges.
