• Build The Agentic Platform: Design, develop, and operate the backend systems that power Arbiter’s agent-driven care orchestration workflows, including service orchestration, inference pipelines, and automation primitives. • Production AI Systems: Ship and maintain production-grade AI systems that automate complex clinical and administrative workflows, with real customer dependency and strict reliability, latency, and correctness requirements. • Platform Architecture & Scalability: Contribute to the architectural design of Arbiter’s AI-driven platform, emphasizing modularity, extensibility, scalability, and clean integration with EMRs, data systems, and external services. • Inference & Backend Reliability: Ensure high performance, low latency, and fault tolerance across backend services and AI inference pipelines through strong system design, monitoring, and operational best practices. • Infrastructure & Deployment Excellence: Implement and uphold best practices for CI/CD, testing, observability, and deployment of backend and AI systems in production environments. • Cross-Functional Execution: Partner closely with data scientists, product managers, clinical experts, and other engineers to translate ambiguous, high-impact problems into scalable technical solutions. • Technical Leadership & Mentorship: Mentor engineers, contribute to internal documentation and standards, influence technical direction, and raise the overall engineering bar. • Ownership & On-Call: Take end-to-end ownership of critical systems, including participating in on-call rotations and leading incident resolution when production issues arise.

• Design and implement high-performance Golang microservices for e-commerce checkout, account management, and fraud mitigation. • Take ownership of components and features within backend systems, ensuring reliability, scalability, and maintainability. • Build, test, monitor, and maintain critical integrations and infrastructure. • Develop and support robust internal and external APIs with high throughput and low latency requirements. • Collaborate closely with Product, Design, and Data teams to deliver technical solutions aligned with user and business goals. • Participate in code reviews, share knowledge with teammates, and uphold engineering best practices. • Drive projects from implementation to production deployment with a focus on quality and operational readiness. • Contribute to ongoing improvements in system performance, observability, and CI/CD workflows. • Explore and help implement AI-powered capabilities within our systems and workflows, including agentic tools and intelligent automation. • Support a collaborative, inclusive engineering culture through thoughtful communication and continuous improvement.

• Design and ship high-performance Python services and GenAI features, including RAG pipelines, agents, and tool-calling on a daily basis • Architect and optimize RESTful APIs using frameworks such as FastAPI, ensuring sub-second latency for complex AI-driven products • Own the entire product lifecycle from idea to production, working within autonomous pods where you lead the architecture alongside DevOps and UX teams • Collaborate with cross-functional teams, including ML and Data engineers, to transform raw data into intelligent business value • Stay updated with the latest developments in Python and AI technologies, proactively proposing and implementing innovative solutions to keep the product ahead of the curve

• Praca wyłącznie przy nowym produkcie (greenfield). • Ścisła współpraca z Head of Architecture. • Implementacja backendowych serwisów zgodnie z ustaloną architekturą. • Budowa skalowalnych, cloud-native usług. • Praca z deterministyczną, calculation-heavy logiką biznesową. • Duży nacisk na testy, wydajność, poprawność i przewidywalność działania systemu.