Role: AI Optimization Engineer Location: Charlotte, NC (Remote eligible; Hybrid preferred for local candidates) Duration: 6+ Months
Position Overview Seeking an experienced AI Optimization Engineer to design, develop, and deploy advanced optimization solutions supporting capital planning and investment decision-making. This role combines Operations Research, Mathematical Optimization, Cloud Engineering, and AI-driven technologies to deliver scalable, explainable optimization services for utility planning initiatives.
Key Responsibilities
Develop and optimize Mixed-Integer Linear Programming (MILP) models using Python frameworks such as Pyomo, PuLP, OR-Tools, and solver technologies including Gurobi, HiGHS, CBC, and CPLEX.
Translate business rules, budget constraints, resource limits, timing dependencies, and investment priorities into optimization models.
Build scalable optimization services using AWS technologies including Batch, Fargate/ECS, Lambda, Step Functions, S3, RDS, and SageMaker.
Integrate predictive analytics outputs (Probability of Failure, Remaining Useful Life, Risk Exposure) into optimization workflows.
Develop automated testing, validation, performance tuning, and explainability features for optimization models.
Create reusable optimization components, APIs, frameworks, and engineering accelerators.
Leverage GitHub, GitHub Copilot, AI agents, and automation frameworks within the software development lifecycle.
Support Infrastructure as Code (IaC) practices using Terraform.
Top 3 Required Skills
Mathematical Optimization / MILP
Strong experience with optimization modeling, Pyomo or PuLP, and commercial/open-source solvers.
Operations Research
Deep understanding of linear and integer programming, resource-constrained optimization, trade-off analysis, and model diagnostics.
AWS Cloud Engineering
Experience with AWS services including Batch, Fargate/ECS, Lambda, Step Functions, S3, RDS, and SageMaker.
Qualifications
Bachelor's or Master's degree in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, Information Technology, or related field.
5+ years of professional experience developing optimization models or decision-support applications.
Strong Python development skills.
Experience with cloud platforms, APIs, containers, CI/CD pipelines, and Terraform.
Familiarity with AI-assisted development tools, AI agents, and large language model-based solutions.
Utility, asset management, capital planning, or portfolio optimization experience is a plus.
Interview Process
2-3 interview rounds, including Cognizant and client interviews.
Primarily virtual interviews; final round may be conducted at the nearest office location.
Candidates must participate on video, present photo ID, use a noise-free environment, and refrain from using AI assistance during interviews.
Applicant Notices & Disclaimers
For information on benefits, equal opportunity employment, and location-specific applicant notices, click here
At SPECTRAFORCE, we are committed to maintaining a workplace that ensures fair compensation and wage transparency in adherence with all applicable state and local laws.This position's pay range is $68.00/hr - $70.00/hr.
