Senior Backend AI Engineer
Listed on 2026-03-01
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Software Development
AI Engineer, Cloud Engineer - Software, Software Engineer, Backend Developer
Arbiter is the AI-powered care orchestration system that unites healthcare. We are launching our best-in-class, patient-facing agentic platform to optimize patient outcomes through a unique multimodal approach. We optimize complex healthcare workflows that interface with patients using the latest agentic AI approaches to optimize patient outcomes, and we combine it with a sophisticated platform to serve this agentic layer are looking for expert engineers and leads to join our team and help us push the frontier of what’s possible with agentic workflows in healthcare.
Backed by one of the largest seed rounds in health tech history and operators who bring the expertise and distribution to scale nationally, we’re building the connected infrastructure healthcare should have had all along.
Our Engineering Culture & ValuesWe are a high-performing group of engineers dedicated to delivering innovative, high-quality solutions to our clients and business partners. We believe in:
Engineering Excellence: Taking immense pride in our technical craft and the products we build, treating both with utmost respect and care.
Impact-Driven Development: Firmly committed to engineering high-quality, fault-tolerant, and highly scalable systems that evolve seamlessly with business needs, minimizing disruption.
Collaboration Over Ego: Valuing exceptional work and groundbreaking ideas above all else. We seek talented individuals who are accustomed to working in a fast-paced environment and are driven to ship often to achieve significant impact.
Continuous Growth: Fostering an environment of continuous learning, mentorship, and professional development, where you can deepen your expertise and grow your career.
As a Senior Backend AI Engineer, you will design, build, and operate the backend AI systems that power Arbiter’s intelligent care orchestration platform. Owning critical parts of our agentic infrastructure, from low-latency inference pipelines to workflow automation and service orchestration, working closely with product, data, and clinical partners to ship production-grade AI systems with real customer dependency.
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.
5 + years of hands-on experience building and operating production backend systems, recent experience with AI-powered services and automation workflows, in high-availability environments.
Computer Science or Engineering degree, or equivalent practical experience.
Experience building and maintaining large-scale Python codebases with strong opinions on structure, quality, and tradeoffs.
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