• Focus on the AI logic required to convert unstructured call summarizations into high-quality, clinical-grade SOAP (Subjective, Objective, Assessment, and Plan) notes. • Help build Arine's prompt generation, defining guardrails and determining how the agent should respond to questions or comments from the stakeholder it is talking to.

• 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.