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Salary
≈ $73k – $134k per year (Estimated)
Location
In office (Austin)
Seniority
Middle · 3+ years exp
Visa
H-1B filings in 12 months: 9 · green card filings: 4

Confirmed on the employer's own hiring board on Oct 28, 2026. First seen by Alion on Oct 20, 2026.

Overview
Company
Impact
Profile match
Electric Power Engineers (EPE) is a power systems engineering and consulting firm serving utilities, grid operators, renewable energy developers and other power and energy clients. Its services span utility engineering, transmission planning, grid and resource integration, reliability and compliance, digitalization and grid analytics, and it works on grid software with its sister company ENER-I.AI. The firm reports more than 50 years of work for clients worldwide and has teams in Texas, Panama, Mexico City, Toronto and Beirut. The company is headquartered in Austin, Texas, United States.

Overview

We are designing the grid of the future!

Be a part of an innovative team shaping the grid of the future through advanced energy intelligence. For more than half a century, Electric Power Engineers (EPE) has partnered with power and energy clients across the globe, providing consulting expertise and energy intelligence software solutions for complex engineering and grid modeling challenges. As leaders in the renewables space, we are focused on building a modern, secure, and resilient grid. Join us in making an impact on the communities we serve and the environment in which we live. Together we can transform the future of energy.

Responsibilities

Join us in leading the change!

We are seeking a Power Systems Optimization Engineer to join the EPE software team. This role pairs transmission planning expertise with mathematical optimization to solve some of the hardest problems in grid planning: selecting least-cost, technically sufficient mitigation portfolios and quantifying their economic value.

You will design, prototype, and productionize optimization methods for problems that are large, non-linear, and mixed-integer by nature, such as choosing which network upgrades, storage, or operational measures resolve violations across many scenarios and contingencies. You'll work closely with planners, software developers, and product owners to turn these methods into reliable tools inside our planning platform.

How you can make an impact:

  • Mitigation portfolio optimization: Formulate and solve problems that select least-cost combinations of transmission upgrades, storage, reconfiguration, and other mitigations to resolve thermal, voltage, and stability violations across multiple cases, seasons, and contingencies.
  • Economic analysis: Build methods for cost allocation, benefit-cost and production-cost-informed evaluation, and comparison of alternative portfolios to support planning and interconnection decisions.
  • Non-linear & mixed-integer modeling: Develop MILP/MINLP formulations, AC/DC power flow relaxations and linearizations (e.g., DC/PTDF, LODF, SOCP), decomposition approaches (e.g., Benders), and heuristics that scale to large real-world systems.
  • Algorithm development to production: Prototype in Python, validate against full AC power flow results from industry tools, and work with developers to deploy methods as robust, scalable services.
  • Validation & benchmarking: Verify that optimized portfolios solve the violations when re-simulated; quantify optimality gaps, runtime, and sensitivity to assumptions.
  • Collaboration: Partner with transmission planners to capture real-world constraints (lead times, outage feasibility, cost estimates, planning criteria) and translate them into model constraints and objectives.
  • Client support & communication: Explain optimization results, trade-offs, and assumptions to engineers, clients, and stakeholders; support onboarding and tailored deployments.
  • Documentation: Write methodology papers, model formulations, and validation reports that help engineers and clients trust the results.

Qualifications

Bring your passion, here's what’s needed:

  • Master's degree or PhD in Electrical Engineering, Operations Research, Applied Mathematics, or a related field, with a focus on power systems and/or optimization. A Bachelor's with equivalent experience will be considered.
  • 3+ years of experience applying optimization to power systems problems (e.g., transmission expansion planning, optimal power flow, unit commitment, resource or portfolio planning), in industry or research.
  • Strong foundation in mathematical optimization: linear, mixed-integer, and non-linear programming, convex relaxations, and decomposition methods.
  • Proficiency in Python and at least one optimization modeling framework (e.g., Pyomo, JuMP, CVXPY, PuLP, gurobipy) and commercial or open-source solvers (e.g., Gurobi, CPLEX, Xpress, HiGHS, Ipopt).
  • Solid understanding of power flow, contingency analysis, and transmission planning concepts, including the US transmission system and ISO/RTO structures.
  • Strong communication skills: able to explain complex models, assumptions, and results to engineers and non-technical audiences.
  • Excellent problem-solving skills, especially in diagnosing infeasibility, numerical issues, and scaling challenges in large models.

Preferred Qualifications:

  • Hands-on transmission planning or interconnection study experience (steady-state, short circuit, dynamic stability) using tools such as PSS/E, PSLF, PowerWorld, TSAT, or TARA.
  • Experience with transmission expansion planning, network upgrade cost allocation, or interconnection cluster studies (e.g., SPP DISIS, MISO DPP, PJM cycle studies).
  • Experience with production cost or capacity expansion models (e.g., PLEXOS, PROMOD, GridView, Aurora, PowerSIMM) and economic planning metrics (APC, adjusted production cost, benefit-cost ratios).
  • Experience with stochastic or robust optimization and scenario-based planning under uncertainty.
  • Familiarity with power systems optimization packages (e.g., PowerModels.jl, pandapower, PyPSA, MATPOWER).
  • Software engineering practices: Git, testing (pytest), code review, and deploying models in cloud or distributed environments.
  • Knowledge of machine learning methods used to accelerate optimization (e.g., surrogate models, warm-starting, constraint screening).
  • Publications or open-source contributions in power systems optimization.

Be a part of an innovative team shaping the grid of the future through advanced energy intelligence. For more than half a century, Electric Power Engineers (EPE) has partnered with power and energy clients across the globe, providing consulting expertise and energy intelligence software solutions for complex engineering and grid modeling challenges. As leaders in the renewables space, we are focused on building a modern, secure, and resilient grid. Join us in making an impact on the communities we serve and the environment in which we live. Together we can transform the future of energy.

How we support you:

  • Comprehensive health and wellness benefits including medical, dental, and vision with 100% premium coverage for you
  • Generous PTO and paid holidays
  • MyShare Employee Ownership Program
  • Work with industry leaders
  • 401K, up to a 4% match (100% vested from day 1)

Location: This position will be Remote.

Travel: Occasional travel may be needed (10% or less)

EPE is an equal opportunity/AA/Disability/Veteran employer. The EEO is the Law poster, and its supplement are available using the following links: EEOC is the Law Poster

Third-Party Recruiting Notification

EPE does not accept unsolicited resumes from third-party recruiters. Any unsolicited third-party resumes forwarded by recruiters to EPE via our career page or to any of our managers or employees will be considered public information, may be treated as a direct application from the person identified in the resume, and will not be eligible for placement fee payment to the agency. EPE will not pay a fee to a third-party recruiter or agency without a previously signed third-party agreement and has not coordinated their recruiting activity with the appropriate member of the Talent Acquisition team.

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