• Build and improve AI-powered applications and internal tools • Rapidly prototype, experiment, and iterate across client and internal projects • Implement workflows that use LLMs, retrieval systems, agents, and structured outputs • Contribute to shared platform work and reusable tooling • Turn prototypes into reliable, client-ready systems • Conduct research, benchmarking, testing, and evaluation of new approaches • Own smaller projects or sub-projects with guidance from the team • Take ownership of deliverables and help deliver work that meets client needs • Write and maintain clear internal documentation

• You develop and operate AI-native features end-to-end — with a focus on quality, safety, latency, and cost efficiency. • You build agentic applications and chatbots, including tool use, stateful workflows, and (multi-)agent orchestration. • You establish standards and best practices for how we develop, evaluate, and deploy AI systems. • You work closely with product and engineering leadership to translate business requirements into technical solutions. • You actively shape experimentation workflows and long-term AI roadmap decisions.

• Create solutions for customers: Architect and implement intelligent LLM-powered ETL pipelines from scratch to transform unstructured client data into concrete, structured solutions. • Build individual agents : Develop autonomous, multi-agent systems using state-of-the-art frameworks to automate complex, multi-step human business processes. • Keep the quality high : Design and maintain robust evaluation frameworks to systematically quantify AI performance and serve as the gatekeeper of quality for production systems. • Own the whole cycle : Build and deploy high-performance RAG systems and wrap the AI logic into performant, production-ready microservices (e.g., FastAPI). • Grow with your team : Actively engage in creative brainstorming sessions and technical design discussions with teammates to challenge assumptions, jointly solve problems, and grow the team's collective knowledge.

• Develop and maintain our full‑stack applications within a modern JavaScript/TypeScript ecosystem • Design and implement scalable backend services with Node.js and Nest.js • Implement high‑performance frontend solutions using React.js and Next.js • Design and optimize relational databases (PostgreSQL, MySQL, MS SQL) • Containerize and orchestrate services using Docker and Kubernetes • Develop and integrate REST APIs • Build and operate data pipelines, feature stores and ML workflows for our agentic systems • Develop, train and evaluate machine learning models for marketing use cases (attribution, targeting, forecasting, anomaly detection) • Implement retrieval‑augmented generation (RAG) pipelines (embeddings, vector stores, re‑ranking) • Set up and maintain LLM evaluation frameworks, prompt optimization and systematic quality benchmarks • Apply code harnesses (notably Claude Code and Codex) in the daily development process — from planning through implementation to code review • Collaborate closely with the founding team on the product architecture of agentic systems