Backend Software Engineer – Matching and Scheduling Optimization

Backend Software Engineer – Matching and Scheduling Optimization

Location:

Palo Alto, CA (Hybrid: Tuesday through Thursday onsite)

As a Backend Software Engineer focused on Optimization, you will architect and implement high‑performance backend services that power Sage’s care‑logistics and navigation engine. Your work will translate complex real‑world constraints into well‑structured optimization problems that can be solved at scale, directly impacting patient access and provider efficiency.

• Design and build backend services that support scheduling, matching, and resource‑allocation optimization for patient care pathways.
• Formalize operational requirements (clinical constraints, time windows, continuity rules, workforce capacity) into parameters for structured optimization problems.
• Implement high‑performance algorithms (job scheduling, optimal matching, constraint solving) and integrate them into production services.
• Optimize for performance: reduce latency, improve throughput, increase reliability, and ensure consistent SLA adherence.
• Build well‑structured APIs, data models, and distributed service components that support real‑time decisioning.
• Profile, benchmark, and tune services to handle the scale and unpredictability of healthcare operations.

• Collaborate with data scientists to transform prototypes into reliable, production‑grade services.
• Partner with product and infra teams to align technical constraints with business requirements, regulatory needs, and system architecture.

• Build observability into all systems with a strong focus on reliability.
• Continuously refine algorithms and system design based on new data sources, operational feedback, and product expansion.

• Bachelor’s or Master’s degree in Computer Science, Engineering, Operations Research, or a related field.
• 5+ years of experience in backend or systems engineering in production environments.
• Strong experience with Java or another high‑level programming language (e.g. Python, Go, C++, or Rust).
• Demonstrated experience building low‑latency, high‑throughput, and high‑reliability backend systems.
• Familiarity with cloud environments (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
• Excellent communication skills and ability to collaborate with cross‑functional teams in a domain‑heavy environment.

• Experience with combinatorial optimization and constraint‑solving algorithms (optimal dispatch, routing, linear and mixed integer linear programming, or metaheuristic algorithms).
• Familiarity with optimization libraries such as OR‑Tools, Gurobi, CPLEX, or similar tools.
• Background in logistics, scheduling, workforce optimization, or healthcare operations.
• Experience with real‑time systems where reliability, interpretability, and resilience are critical.

• Work on deeply meaningful, high‑impact problems that directly improve patient access and provider efficiency.
• Join a high‑performing engineering team where ownership is large and impact is immediate.
• Competitive compensation, meaningful equity, and comprehensive benefits.
• Hybrid work culture with deep collaboration across engineering, product, and clinical teams.
• The opportunity to define the core optimization engine that powers the future of healthcare operations.

• Initial review and a 30–60 minute take‑home technical assessment.
• Hiring manager and/or engineer chats.
• Onsite interview loop (including a team lunch!).
• Reference check and offer.

Seniority level:
Mid‑Senior level |

Employment type:

Full‑time | Job function:
Engineering and Information Technology | Industries:
Hospitals and Health Care