Senior Power Systems Engineer

Bidgely

About The Position

Bidgely is seeking a Senior Power Systems Engineer to build software product capabilities for utility grid capacity, scenario, and interconnection studies. The role combines power-flow and grid-planning expertise with software engineering. The engineer will own the electrical correctness of product results while working with Grid portfolio developers. The role reports to the Director of Engineering, with a dotted line to the Director of Product, Grid Planning. The engineer will evaluate, recommend, integrate, and operate an existing open-source or licensed power-flow solver; Bidgely does not plan to develop its own solver. The role also owns the capacity digital twin, including the data requirements and repeatable utility integrations that turn connectivity models into validated, versioned grid models. On top of the twin and solver, the engineer will build product capabilities for scenarios, forecasting, real loading, and interconnection studies. The position emphasizes validating results against sanctioned planning tools and field data, documenting assumptions and data lineage, and explaining differences to utility planners and engineers. It also involves rapidly prototyping planning capabilities using utility data and turning successful approaches into production features. The product is focused on grid capacity, not real-time operations or asset health.

Requirements

BTech or MTech in Electrical Engineering; a power systems specialization is preferred.
At least 5 years of experience in distribution system modeling or power systems analysis, including personally building models from imperfect source data.
Hands-on experience with at least one distribution power-flow tool: OpenDSS, CYME, Synergi, PowerFactory, PSS®SINCAL, or an ADMS power-flow engine.
Knowledge of unbalanced three-phase distribution load flow, including voltage bases, phase representation, equipment models, thermal and voltage limits, and reverse flow.
Working knowledge of the distribution capacity-planning cycle and what makes planners accept or reject a result.
Ability to benchmark one modeling tool against another and explain differences.
Ability to turn raw utility data into a working study quickly, while making shortcuts explicit.
Ability to work in a production codebase alongside software developers, under code review and with tests and CI.
Ability to judge whether an electrical result is credible and explain it to utility planners and engineers.

Nice To Haves

Experience running or reviewing load or DER interconnection studies covering screening, system impact, contingency performance, and service options.
Utility consulting or EPC experience with exposure to multiple utilities.
Experience with large-load or data-center interconnection, including phased energization and onsite generation or storage.
Experience with flexible or non-firm interconnection, including conditional service, curtailment envelopes, and flexible connection agreements.
Experience with connectivity model conversion at scale from CIM, GIS, or vendor exports.
Experience with AMI interval data and 8760 forecasting, DER hosting capacity, and N-1 and switching analysis.
Python skills, including profiling numerical code at scale.
Experience evaluating or integrating a commercial solver SDK.

Responsibilities

Evaluate open-source and licensed power-flow engines using real feeders, benchmark their results, quantify differences, and recommend a solver based on evidence.
Document solver capabilities and limitations at Bidgely's scale, integrate the selected engine into the product, and ensure it fits with Grid Intelligence.
Build and maintain the capacity digital twin as a repeatable pipeline that converts utility connectivity models into validated, versioned grid models.
Define the network, asset, AMI, SCADA, and forecast data requirements for the twin, including minimum viable data sets and handling for data gaps.
Build repeatable utility integrations for connectivity model exports in CIM, GIS, and vendor formats, as well as SCADA and AMI data.
Engineer meter–transformer–phase confidence and SCADA calibration into the twin; keep it focused on capacity and versioned against the utility's system of record.
Build data-quality exception handling that explicitly flags connectivity gaps rather than allowing silently incorrect results.
Build scenario capabilities for base, future, flexibility, contingency, and switching cases on the twin, with comparable results.
Translate load, DER, EV, electrification, and large-load forecasts into study-ready asset-level 8760 P/Q and phase cases, including low, base, and high ranges and year of need.
Engineer reliable, repeatable 8760 and time-series scenario execution at production scale.
Build a real-loading model for hourly, per-phase loading on assets from AMI-derived appliance-level demand, reconciled to SCADA and accounting for phase, coincidence, unmetered load, and losses.
Build product capabilities for utility interconnection studies for new load and DER using the capacity digital twin and power-flow solution.
Engineer interconnection workflows for 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 capabilities, including phased energization, 8760 P/Q profiles, cooling and commissioning cases, and onsite generation, storage, and UPS.
Build flexible interconnection options covering firm, phased, conditional, and flexible service, with import, ramp, and curtailment envelopes.
Make failed cases productive by proposing repairs or alternate connection paths and packaging engineer-ready cases for utility-authoritative studies.
Own technical design of the power-flow, twin, and study layer in collaboration with developers, addressing scale, failure handling, and observability.
Build QA and regression tests that verify changes do not alter results unexpectedly; benchmark results against sanctioned planning tools and field expectations and explain divergences.
Document assumptions, data lineage, and model versioning to standards suitable for planner review and eventual regulatory filings.
Run rapid proofs of concept for planning capabilities using utility data, label shortcuts, and move successful approaches into production.
Lead technical validation of pilots and proofs of value by defining acceptance tests, producing results with the product, and defending them to utility planners and engineers.
Partner with Product on requirements and roadmap by determining whether product results are electrically correct, and work with the GM, Grid and Data Science on evidence supporting utility adoption.