Backend Software Engineer - Matching and Scheduling Optimization

Sage Care

Sage Care

Software Engineering
Palo Alto, CA, USA · Toronto, ON, Canada
Posted on Nov 21, 2025

Location

HQ

Employment Type

Full time

Department

Engineering

Backend Software Engineer – Matching and Scheduling Optimization

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

About Us

At Sage Care, we’re transforming healthcare with AI-powered solutions that streamline care navigation and optimize care delivery for health systems. Our technology makes it easier for patients to access the right care, enables providers to focus on the patients who need them most, and improves operational efficiency across the entire system. Built by experts from Carbon Health, Apple, and Uber, our platform automates triage, enhances provider-patient matching, and maximizes appointment and care capacity.

We’re on a mission to make healthcare more accessible, efficient, and equitable for everyone — and optimization engineering is core to that mission.

Role Overview

As a Backend Software Engineer focused on Optimization, you will help architect and implement the high-performance backend services that power Sage’s care-logistics and navigation engine. You’ll help translate complex real-world constraints ranging from provider schedules, patient needs, and operational workflows, into well-structured optimization problems that can be solved at scale.

This role blends algorithmic thinking with production-level engineering. You’ll work closely with engineers, data scientists, and product teams to translate healthcare workflows into formalized matching and scheduling problems, then build the backend services to solve them in real time. Your work will directly impact how health systems match patients to care, increase throughput, reduce bottlenecks, and improve access across large provider networks.

Key Responsibilities

Optimization Design & Implementation

  • Design and build backend services that support scheduling, matching, and resource-allocation optimization for patient care pathways.

  • Formalize operational requirements like clinical constraints, time windows, continuity rules, and workforce capacity into parameters for well-structured optimization problems.

  • Implement high-performance algorithms (e.g., job scheduling algorithms, optimal matching, constraint solving) and integrate them into production services.

Backend Engineering Excellence

  • 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.

Cross-Functional Collaboration

  • 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.

Monitoring, Reliability & Continuous Improvement

  • Help build observability into all systems with a strong attention to reliability.

  • Continuously refine algorithms and system design based on new data sources, operational feedback, and product expansion.

Required Qualifications

  • 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.

Preferred Qualifications

  • Experience with combinatorial optimization and constraint-solving algorithms using optimal dispatch, routing, linear and mixed integer linear programming, or metaheursitic algorithms (e.g. evolutionary 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.

Why Join Sage Care

  • 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.

Interview Process

Our interview process typically includes:

  1. Initial review and a 30–60 minute take-home technical assessment

  2. Recruiter conversation

  3. Hiring Manager and/or Engineer chats

  4. Onsite interview loop (including a team lunch!)

  5. Reference check and offer