Director of Engineering, WFM Operations Research (Individual Contributor)

Fidelity is building a modern, in-house Workforce Management (WFM) platform. You will own and build a constraint-solver foundation for the Contact Center Workforce Management schedule optimization engine leveraging a CP-SAT/OR-Tools engine at enterprise scale and reliability. This role is deeply a hands-on role, you will design, develop, and implement advance optimization models and algorithms to solve complex workforce planning and scheduling problems.

Responsibilities

Research, design, and develop optimization models for contact center workforce planning, scheduling and resource allocation; Design and implement the schedule optimization engine using OR-Tools/CP-SAT; Own the constraint model end to end: formalize business rule into a solvable, maintainable model; Build the production-grade solver as a service within the WFM platform that meets latency targets for real forecast group volumes; Define and validate schedule quality metrics (coverage attainment, constraint violations, solve time, solution stability across re-solves) and instrument the service so quality can be monitored in production; Build and execute tests and validation of optimization algorithms to deliver performance, scalability, and accuracy; Collaborate with architects and engineering teams to integrate optimization models into an enterprise-grade optimization engine of the workforce management platform; Effectively communicate and present findings, methodologies, and results to engineering and business stakeholders; Partner with workforce-planning and real-time-analyst stakeholders to validate that generated schedules are operationally usable

Requirements

Bachelor’s of master’s degree in operations research, Mathematics, Computer Science, or a related field; 5+ years of experience in applying operations research techniques to real-world problems; Hands-on production experience with OR-Tools, CP-SAT, or a comparable constraint-programming / mixed-integer-programming solver; Strong foundation in linear programming, integer programming, or stochastic optimization; Proficiency in Java, Python, or C++; Experience with cloud platforms such as AWS, GCP, or Azure; Experience working with large datasets and solving large scale optimization problems; Direct experience modeling and solving workforce or resource scheduling problems; Working knowledge of WFM domain; Knowledge of distributed systems and event-driven architecture

Nice to have

Prior experience building scheduling or optimization capability at a WFM SaaS provider or a large in-house contact center operations team; Familiarity with other solver technologies (e.g., Gurobi, CPLEX, OptaPlanner); Experience in applying ML, AI, or Data Science