Affordability Theory of Constraint (TOC) Engineer II

RTX•Tucson, AZ

9d•$68,900 - $131,100•Onsite

About The Position

Affordability Engineering at Raytheon focuses on optimizing solutions across the product lifecycle by integrating technical performance, design choices, manufacturing behavior, supplier inputs, sustainment considerations, and readiness metrics into a unified cost and throughput framework. The Affordability Theory of Constraint (TOC) Engineer II supports the development and execution of discrete event simulation (DES) models to identify system constraints, characterize resource interactions, quantify throughput impacts, and assess cost and schedule sensitivities. This work enables program leadership to make data-driven decisions that balance cost, performance, schedule, and mission needs. This is an onsite position based in Tucson, Arizona. The role requires U.S. citizenship and an active, existing DoD Top Secret clearance after the first day.

Requirements

Typically requires a STEM degree and at least 2 years of relevant experience, unless prohibited by local laws or regulations.
Experience in Systems Engineering, operations research, Industrial Engineering, or a related analytical discipline.
Experience working with structured datasets such as Excel, CSV files, or databases for data analysis and/or model input preparation.
Experience building or using discrete event simulation tools such as ExtendSim, Simio, Arena, or similar platforms.
U.S. citizenship is required because only U.S. citizens are eligible for the required security clearance.
Ability to obtain and maintain a U.S. government-issued security clearance; an active and existing DoD Top Secret clearance is required after day one.

Nice To Haves

Experience presenting to internal stakeholders.
Experience analyzing production and supply chain performance, including queueing behavior, yields, resource constraints, rework or repair flows, and operational risk drivers.
Experience conducting scenario analyses, such as parameter sweeps, sensitivity studies, or Monte Carlo simulations, using structured data inputs such as Excel or databases.
Experience with data visualization and analytics tools such as Python, Power BI, Tableau, or JMP to interpret simulation outputs and support lifecycle cost, affordability, or readiness assessments.
Experience collaborating with cross-functional teams and supporting system-of-systems evaluations across manufacturing, supply chain, engineering, and program teams.

Responsibilities

Develop, execute, and maintain discrete event simulation models to analyze throughput, queueing behavior, cycle time, resource constraints, and system bottlenecks.
Prepare model input datasets using validated engineering, operations, supplier, and sustainment data.
Identify and characterize constraints across production lines, supply chain flows, and sustainment or repair loops.
Analyze how design decisions, yield variations, staffing assumptions, and supplier performance affect system throughput and affordability.
Conduct multi-scenario studies, sensitivity analyses, and parameter sweeps.
Document model assumptions, boundaries, and data traceability to ensure credibility and repeatability.
Support affordability assessments, including lifecycle cost modeling, business case analyses, and readiness or availability studies.
Collaborate with Affordability Leads and cross-functional teams to align model outputs with program requirements.
Update model inputs as new data becomes available to ensure accurate reflection of system behavior.

Benefits

Relocation assistance
Medical insurance
Dental insurance
Vision insurance
Life insurance
Short-term disability insurance
Long-term disability insurance
401(k) match
Flexible spending accounts
Flexible work schedules
Employee assistance program
Employee Scholar Program
Parental leave
Paid time off
Holidays
Potential annual short-term and/or long-term incentive compensation, subject to eligibility and other factors