Build the future of enterprise AI with us.

About the role

We are building next-generation AI-powered commerce infrastructure and intelligent platforms that help businesses become AI-agent ready. Our products combine LLMs, data pipelines, automation systems, agentic workflows, and scalable cloud infrastructure to solve real-world commerce and enterprise problems.

Key responsibilities

• Design, develop, and deploy scalable AI/ML systems, intelligent automation pipelines, and production-grade AI services.
• Architect and optimize LLM-powered applications, including Retrieval-Augmented Generation (RAG) systems, AI agents, multi-agent workflows, and orchestration frameworks.
• Develop robust backend services and APIs using Python, Node.js, and TypeScript to support AI-driven applications.
• Integrate and manage enterprise AI models and platforms such as OpenAI, Claude, Grok, Llama, and vector database technologies.
• Build and maintain data pipelines, embedding workflows, semantic search capabilities, recommendation engines, and knowledge retrieval systems.
• Collaborate cross-functionally with product, engineering, and design teams to deliver scalable AI-first products and features.

About the role

A modern SaaS platform that helps brands understand and improve how they appear across answer engines and digital commerce experiences. The product combines analytics dashboards, integrations, background processing, product/catalog workflows, and evidence-backed reporting. The stack includes Next.js, TypeScript, Python, FastAPI, PostgreSQL, Docker, GitHub Actions, and cloud deployment.

Key responsibilities

• Building and improving product features across the Next.js frontend and FastAPI backend.
• Working on commerce features such as product catalogs, competitor products, imports, product visibility, attribution, and integrations.
• Designing maintainable APIs, data models, background jobs, and reusable UI components.
• Using AI-assisted development tools to explore the codebase, plan changes, implement features, write tests, and debug issues.
• Reviewing AI-generated code critically instead of accepting it without validation.
• Writing unit, component, and integration tests.
• Maintaining clear Git history and working with branches, pull requests, reviews, and GitHub Actions.
• Improving code organization, documentation, reliability, and developer experience.
• Participating in technical discussions about architecture and implementation trade-offs.