Note: Fidelity will not provide immigration sponsorship for this position.

The Role 

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.  

Key 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. 

Required Qualifications 

• 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 

Preferred Qualifications 

• 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