Forward Deployed Engineer Jobs in Pittsburgh, PA

The Team

ConvergeCONSUMER ™ is a product-driven business that combines differentiated consumer data, predictive modeling, and mathematical optimization to help organizations make faster, smarter, and more precise decisions. We operate with the speed and focus of a product company within one of the world's largest professional services firms.

Our platform enables granular decision-making across pricing, promotion, forecasting, assortment, and other mission-critical business domains. We deliver scalable, reusable decision intelligence assets that integrate seamlessly into client environments and drive measurable performance improvement.

Are you an experienced Product Support Engineer who has supported the development of world-class software or digital products? Are you looking for an opportunity to expand your scope and support products used by some of the biggest and most influential businesses around the world? If the answer to these questions is yes, we would like to talk with you.

Recruiting for this role ends on 6/23/2026.

Work you'll do

Are you an experienced technical leader who has deployed advanced analytics or optimization-based products into complex enterprise environments? Are you energized by translating sophisticated decision engines into real-world impact for global clients? If so, we would like to talk with you.

We are seeking a Forward Deployed Engineering Manager to lead client delivery for pricing and promotion optimization solutions. This role sits at the intersection of optimization, data engineering, and enterprise deployment.

You will be responsible for translating complex business requirements into production-ready optimization configurations and ensuring successful implementation of ConvergeCONSUMER's pricing and promotion engines within client environments.

Key Responsibilities:

• Lead end-to-end deployment of pricing and promotion optimization solutions in client environments.
• Translate business objectives, pricing structures, and operational constraints into structured optimization inputs and system configurations.
• Configure and operationalize existing optimization engines rather than building net-new modeling frameworks from scratch.
• Integrate client first-party data, demand forecasts, elasticity models, and other inputs into scalable optimization workflows.
• Utilize solvers such as CPLEX, GUROBI, or similar technologies to execute and validate large-scale linear and mixed-integer optimization problems.
• Partner with data engineering teams to validate pipelines, resolve data quality issues, and ensure reliable model inputs.
• Design and run scenario analyses that enable stakeholders to evaluate trade-offs across margin, volume, revenue, and other key performance indicators.
• Ensure optimization outputs are feasible, aligned with guardrails, and ready for operational execution.
• Identify and resolve performance bottlenecks related to model runtime, scaling, or infrastructure constraints.
• Provide clear documentation, training, and enablement to drive sustainable client adoption.
• Manage and mentor a team of forward deployed engineers, fostering technical rigor and delivery excellence.
Surface recurring implementation patterns and configuration challenges to inform enhancements to reusable pricing assets.

The successful candidate will possess

• Demonstrated expertise in mathematical optimization including linear programming and mixed-integer programming.
• Hands-on experience using commercial solvers such as CPLEX, GUROBI, or similar tools.
• Practical experience working with price elasticity modeling and integrating demand forecasts into optimization workflows.
• Strong ability to translate business requirements into formal model objectives and constraints.
• Experience troubleshooting model inputs, performance issues, and production deployment challenges.
• Proven leadership experience managing technical teams.
• Strong communication skills with the ability to explain optimization outputs to technical and non-technical stakeholders.
• Experience supporting deployment of solutions in web-based or SaaS architectures.
• Experience implementing pricing or promotion optimization solutions in retail, consumer products, restaurants, or other consumer-facing industries.
• Experience deploying optimization solutions in cloud-native environments.
• Familiarity with revenue growth management processes or pricing governance models.
Experience working in product-oriented delivery teams or asset-based consulting models.

Qualifications

Required:

• Bachelor's degree in Operations Research, Applied Mathematics, Economics, Data Science, Engineering, or a related quantitative field.
• 8+ years of experience delivering optimization, advanced analytics, or decision science solutions in client-facing environments.
• Ability to travel 25%, on average, based on the work you do and the clients and industries/sectors you serve.
• Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future

Preferred:
Advanced degree in Operations Research, Applied Mathematics, Economics, or related discipline.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $134,500-$265,100.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.