Senior Power Systems Engineer

About Bidgely

We are an AI-powered, cloud-based SaaS solution provider that enables electric, gas and water utilities worldwide to personalize customer experiences, optimize grid and customer operations, and accelerate their journey towards the clean energy future. Headquartered in Silicon Valley, we serve some of the biggest names in the energy and utilities industry across the USA, Canada, the EU, the Middle East, India, Japan, Australia and New Zealand. We hold 25+ energy patents, have raised $77M+ in funding, and bring a passion for AI to utilities serving 35M+ customers and meters around the world.

Bidgely Grid Intelligence brings that same data to the distribution grid. It turns AMI-derived, appliance-level demand into a capacity view of the grid that answers how many MW a location can support, and whether a new load or DER can connect there — and on what terms. As electrification, DER adoption and data center growth reshape the grid, utilities need those answers faster and with more confidence than traditional planning cycles allow.

Product overview: https://www.bidgely.com/utilityai/ · Grid: https://www.bidgely.com/solutions/der-grid-planning/

Position: Senior Power Systems Engineer — Grid Model & Power Flow

Role Overview

As a Senior Power Systems Engineer, you are a software engineer with deep power flow and grid planning expertise. You will build the product that lets utilities run capacity, scenario and interconnection studies — you will not run those studies by hand as a consultant would. You own the electrical correctness of everything the product produces, working alongside the Grid portfolio's software developers. Reporting to the Director of Engineering, with a dotted line to the Director of Product, Grid Planning, you will:

• Own how power flow is delivered inside the product: evaluate open-source and licensed solvers, recommend one, and integrate and operate it. We will not write our own solver.

• Build and maintain the capacity digital twin of the grid, including the data requirements and utility integrations that feed it.

• Build the scenario, forecasting, real loading and interconnection study capabilities planners use, on top of the twin and the power flow solution.

• Establish whether results are true: benchmark against sanctioned planning tools and field data, and defend results directly to utility planners and engineers.

• Run quick proofs of concept for grid planning solutions — a new study capability, a solver option or an interconnection approach — on a utility's own data in days, and turn what works into the production path.

Key Responsibilities

Power Flow Solutioning

• Evaluate open-source and licensed power flow engines against real feeders; benchmark results and quantify differences.

• Document what each engine can and cannot do at Bidgely's scale, and make the open-source or license recommendation with evidence.

• Integrate the chosen engine into the product and own its fit with the rest of Grid Intelligence.

Capacity Digital Twin

• Build and maintain the capacity digital twin as a product capability: the engineered pipeline that turns a utility's connectivity model into a validated, versioned grid model the product runs studies on.

• Own the data need: define the network, asset, AMI, SCADA and forecast data the twin requires, the minimum viable data set, and how gaps are handled.

• Build the utility integrations that feed the twin — connectivity model exports (CIM, GIS and vendor formats), SCADA and AMI — and make them repeatable across utilities rather than bespoke per customer.

• Engineer meter–transformer–phase confidence and SCADA calibration into the twin, not as one-off analysis.

• Keep the twin scoped to capacity — not real-time operations or asset health — and versioned against the utility's system of record.

• Build the data-quality exception path so connectivity gaps surface as explicit flags, never as silently wrong numbers.

Scenarios, Forecasting and Real Loading

• Build the scenario capability planners need for electrical studies: base, future, flexibility, contingency and switching cases constructed on the twin and comparable side by side.

• Turn forecasting into study-ready inputs: translate load, DER, EV, electrification and large-load forecasts into asset-level 8760 P/Q and phase cases, with low, base and high ranges and year of need.

• Engineer 8760 and time-series execution so planners can run scenarios at production scale, reliably and repeatably.

• Build the real loading model: hourly, per-phase loading on every asset from AMI-derived, appliance-level demand, reconciled to SCADA, with phase, coincidence, unmetered load and losses handled in the product rather than by hand.

Interconnection Study Capability

• Build the product capability that lets a utility run interconnection studies for new load and DER on the capacity digital twin and the power flow solution.

• Engineer the study workflow: request profile and ramp intake, candidate point-of-interconnection mapping, headroom and hosting capacity screening, and existing-system and contingency impact checks.

• Build large-load and data center modeling into the product: phased energization, 8760 P/Q profiles, cooling and commissioning cases, and onsite generation, storage and UPS.

• Build flexible interconnection into the product: firm, phased, conditional and flexible service options, with import, ramp and curtailment envelopes.

• Make failed cases productive: the product proposes the repair or alternate connection path and packages engineer-ready cases for the utility's authoritative studies.

Engineering Quality and Validation

• Own the technical design of the power flow, twin and study layer, working with the portfolio's developers on performance at scale, failure handling and observability.

• Build the QA and regression suite that proves a change did not move results.

• Benchmark against sanctioned planning tools and field expectation, and explain every divergence.

• Document assumptions, data lineage and model versioning to a standard that survives a planner's review and, eventually, a regulatory filing.

Rapid Proofs of Concept

• Run quick proofs of concept for grid planning solutions on a utility's own data in days, not months: a new study capability, a solver option, or a data center interconnection approach.

• Label every shortcut, and turn the approaches that work into the production path.

Product Validation

• Lead technical validation of pilots and proofs of value: define acceptance tests, use the product to produce the result, and defend it to utility planners and engineers.

• Partner with Product, which owns requirements and roadmap, by establishing whether each result is electrically true.

• Work with the GM, Grid and Data Science on the customer evidence that moves a utility to adopt.

Qualifications & Experience

Educational Background

BTech or MTech in Electrical Engineering; power systems specialisation preferred.

Professional Experience

• 5+ years in distribution system modeling or power systems analysis, including models built personally from imperfect source data.

• Hands-on with at least one distribution power flow tool: OpenDSS, CYME, Synergi, PowerFactory, PSS®SINCAL or an ADMS power flow engine. We expect you to learn the others.

• Preferred, not required: has run or reviewed load or DER interconnection studies, covering screening, system impact, contingency performance and service options.

• Model validation experience: can benchmark one tool against another and explain the differences.

• Has worked in a production codebase alongside software developers, under code review, with tests and CI.

• Can turn a utility's raw data into a working study in days, with shortcuts made explicit.

• Utility consulting or EPC background with multi-utility exposure is strongly preferred.

Technical & Domain Expertise

• Unbalanced three-phase distribution load flow: voltage bases, phase representation, equipment models, thermal and voltage limits, and reverse flow.

• Working knowledge of the distribution capacity planning cycle: what a planner does with a result, and what makes them reject one.

• Strongly preferred: large-load or data center interconnection, including phased energization and onsite generation or storage.

• Strongly preferred: flexible or non-firm interconnection — conditional service, curtailment envelopes and flexible connection agreements.

• Strongly preferred: connectivity model conversion at scale from CIM, GIS or vendor exports; AMI interval data and 8760 forecasting; DER hosting capacity; N-1 and switching analysis.

• Strongly preferred: Python, including profiling numerical code at scale, and experience evaluating or integrating a commercial solver SDK.

Core Competencies

• Grid Expert – Brings a planner's judgment to an engineering team, and knows when a result is wrong before the test does.

• Product Builder – Turns study practice into product capability that utilities run themselves, rather than doing the study by hand.

• Rigorous Validator – Proves a result is right before it reaches a utility: benchmarks against trusted planning tools and field data, and explains every difference.

• Fast Builder – Moves from raw utility data to a credible answer in days, and knows which shortcuts are safe.

• Collaborative Engineer – Raises the grid fluency of the developers around them and works as one team with Product.

Why Join Bidgely?

• Shape how utilities plan the grid through electrification, DER growth and the data center surge.

• Be the grid authority on a product that turns AMI data into planning decisions.

• Competitive compensation, benefits and opportunities for professional growth.

• Work at the intersection of AI, data and power systems engineering.

Ready to Apply?

If you know the distribution grid well enough to defend a power flow result to a utility planner, and you want to build the product that makes those studies faster and more trustworthy, we'd love to meet you.