Focus
Drive rapid prototyping and iteration of AI-powered insight and collaboration features that deliver measurable value to users. Leverage modern LLMs and existing AI ecosystems to build, test, and deploy intelligent capabilities that enhance product experience and decision-making.
Key Responsibilities
AI Systems Design: Architect and implement data preprocessing, embedding, and retrieval pipelines that enable dynamic, context-aware insights across user sessions or product workflows.
RAG Development: Build, refine, and optimize retrieval-augmented generation (RAG) systems using best-in-class LLMs and retrieval frameworks to surface relevant, actionable information.
API & Backend Integration: Develop and maintain Node.js and Python APIs to serve AI-driven insights efficiently to frontend applications (React-based).
Cross-Functional Collaboration: Partner closely with product managers, designers, and data engineers to conceptualize and iterate on intelligent features that enhance user experience and engagement.
Rapid Experimentation: Prototype, validate, and deploy high-impact features quickly using existing AI tools and platforms (e.g., OpenAI, Anthropic, Gemini) to maximize learning velocity and value delivery.
Evaluation & Monitoring: Design and implement automated evaluation frameworks, including model performance benchmarking, regression testing, and continuous improvement pipelines.
Scalable Infrastructure: Collaborate with DevOps and data teams to deploy and scale AI services using cloud-native environments (e.g., Fly.io, Supabase, Kafka, ClickHouse).
Technical Stack
Core: Node.js • Python • React • MongoDB • ClickHouse • Supabase • Kafka (Confluent)
AI Platforms: OpenAI • Anthropic • Gemini
Deployment: Fly.io • Docker • CI/CD
Productivity & Collaboration: Cursor • Claude Code • GitHub Copilot • Notion
Ideal Profile
Experience: 2+ years in AI engineering, applied ML, or full-stack development with a strong focus on LLM-driven systems.
Applied AI Expertise: Familiar with retrieval-augmented generation (RAG), vector search, prompt/context engineering, and fine-tuning workflows.
Builder Mentality: Comfortable experimenting with emerging AI tools, iterating fast, and delivering tangible outcomes with minimal overhead.
End-to-End Ownership: Skilled in bridging data, backend, and frontend layers to deliver AI capabilities that feel seamless to the user.
Collaborative & Product-Minded: Enjoys working across disciplines to turn user problems into elegant, data-driven solutions.
Ready to Apply?
We're excited to hear from you! Send us your resume and tell us why you're the perfect fit for this role.
Questions about the role? Get in touch