- Depending on requirements, products may include AI-embedded features (LLM-powered automation, agentic workflows, intelligent document processing) or may be traditional SaaS built with AI-assisted development practices.

What you will build :

- Production SaaS features : end-to-end from UI to API to data model to deployment

- AI-embedded product capabilities where required : workflow automation, document intelligence, conversational interfaces

- Evaluation and monitoring systems for AI features (quality, latency, cost)

Responsibilities :

- Own full-stack delivery with minimal handoffs

- Integrate LLM APIs (OpenAI, Claude, etc.) into production applications

- Ship MVP-quality increments in 23-week cycles

- Collaborate with stakeholders in English; clarify scope, propose trade-offs, and iterate quickly

- Establish practical engineering standards : version control, testing, CI/CD, observability

Required qualifications :

- Full stack - React/Next.js + Node.js and/or Python; database design; API development

- AI-native workflow - Daily use of AI coding tools (Copilot, ChatGPT, Cursor, etc.) for development, debugging, iteration

- LLM integration - Hands-on experience integrating LLM APIs into real applications (not just prototypes)

- Delivery speed - Proven ability to ship working software in 23-week cycles

- Communication - Fluent English (written and verbal); remote-first collaboration discipline

Nice-to-have :

- B2B SaaS or workflow automation experience

- Agentic workflow design (task decomposition, tool use, state management)

- RAG implementation and evaluation

- Cloud deployment (AWS/GCP), CI/CD, containerization