Senior Power Systems Engineer

Jobgether; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive compensation

Remote work in India

Benefits package

Growth opportunities

Job summary

Jobgether is seeking a power systems expert to drive the productization of distribution system modeling and planning tools. You will build validated grid models, integrate CIM/GIS-based data, and benchmark multiple power flow engines to ensure scalable, accurate results.

You will translate engineering workflows into robust product capabilities, collaborate with software teams, and guide interconnection studies and planning scenarios for wide-scale deployment.

Qualifications

• Experience in distribution system modeling and power flow analysis.
• Hands-on with at least one distribution power flow tool.
• Ability to translate engineering results into scalable product capabilities.
• Experience with data integration using CIM, GIS, or vendor formats.

Responsibilities

• Evaluate power flow engines and benchmark performance.
• Build and maintain digital twins of utility networks.
• Define data requirements for network, asset, AMI, SCADA, forecasting.
• Ensure model accuracy and identify connectivity gaps.
• Develop planning scenarios and 8760 profiles.
• Enable scalable 8760/time-series execution for studies.
• Evaluate new interconnection approaches and hosting capacity.

Skills

Power systems

Distribution modeling

Python

Data integration

CI/CD

Stakeholder comms

Education

Bachelors/Master's in Electrical Engineering

Tools

OpenDSS

CYME

Synergi

PowerFactory

PSS-SINCAL

ADMS

Job description

Accountabilities

• - Power Flow Solutioning: Evaluate open-source and licensed power flow engines using real distribution feeders, benchmark their performance, and recommend the most suitable solution. Integrate the selected engine into the product and ensure it operates effectively at scale.
• - Capacity Digital Twin: Build and maintain a validated, versioned digital representation of utility distribution networks, transforming connectivity models and source data into reliable grid models for planning studies.
• - Utility Data Integration: Define the network, asset, AMI, SCADA, and forecasting data requirements. Develop repeatable integrations using CIM, GIS, and vendor-specific formats, and establish processes for handling incomplete or inconsistent data.
• - Grid Model Accuracy: Engineer meter-to-transformer-to-phase confidence, SCADA calibration, and data-quality exception handling into the product. Ensure connectivity gaps and data limitations are explicitly identified rather than producing misleading results.
• - Scenarios, Forecasting, and Real Loading: Develop planning scenarios covering base, future, flexibility, contingency, and switching cases. Translate load, DER, EV, electrification, and large-load forecasts into study-ready asset-level 8760 P/Q profiles and phase scenarios.
• - Time-Series Execution: Build reliable, repeatable 8760 and time-series execution capabilities that allow planners to run scenarios at production scale.
• - Real Loading Models: Develop hourly, per-phase loading models across grid assets using AMI-derived demand, reconciled with SCADA data and accounting for phase allocation, coincidence, unmetered load, and losses.
• - Interconnection Studies: Build product capabilities for evaluating new load and DER connections, including request intake, point-of-interconnection mapping, hosting capacity screening, headroom assessment, and system and contingency impact checks.
• - Large-Load and Data Center Modeling: Incorporate phased energization, 8760 P/Q profiles, cooling and commissioning scenarios, and onsite generation, storage, and UPS configurations into interconnection studies.
• - Flexible Interconnection: Develop support for firm, phased, conditional, and flexible service options, including import, ramp, and curtailment envelopes. Ensure failed study cases can lead to proposed repairs or alternative connection paths.
• - Engineering Quality and Validation: Own the technical design of the power flow, digital twin, and study layers. Collaborate with software developers on performance, failure handling, observability, and maintainability.
• - Testing and Benchmarking: Establish QA and regression testing processes to ensure changes do not compromise electrical results. Benchmark outputs against trusted planning tools and field data, investigate differences, and document technical assumptions.
• - Rapid Proofs of Concept: Deliver practical proofs of concept using utility data within days, evaluating new study capabilities, solver options, or interconnection approaches. Clearly identify shortcuts and transition successful solutions into production.
• - Product and Pilot Validation: Define acceptance tests, validate pilots and proofs of value, and explain technical results directly to utility planners and engineers. Work with Product, Data Science, and business leadership to establish the evidence needed for adoption.

Requirements

The ideal candidate is an experienced power systems professional who combines strong distribution engineering expertise with a product-building mindset and the ability to work effectively alongside software developers. The following qualifications and capabilities are expected:

• - Bachelor's or Master's degree in Electrical Engineering, preferably with a specialization in power systems.
• - 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, such as OpenDSS, CYME, Synergi, PowerFactory, PSS®SINCAL, or an ADMS power flow engine.
• - Strong understanding of unbalanced three-phase distribution load flow, including voltage bases, phase representation, equipment models, thermal and voltage limits, and reverse power flow.
• - Practical knowledge of distribution capacity planning and how utility planners assess and validate engineering results.
• - Experience benchmarking power flow tools against one another and explaining technical differences.
• - Ability to turn raw utility data into credible working studies within short timeframes while clearly identifying assumptions and limitations.
• - Experience working in production software environments alongside developers, with code reviews, automated tests, and continuous integration.
• - Strong technical judgment and the ability to identify inaccurate or questionable results before they reach customers.
• - Ability to translate engineering and planning practices into scalable product capabilities rather than relying on manual consulting-style studies.
• - Strong collaboration and communication skills, including the ability to explain complex engineering findings to technical and non-technical stakeholders.

Additional Relevant Experience

The following capabilities are strongly preferred:

• - Experience conducting or reviewing load and DER interconnection studies, including screening, system impact assessments, contingency performance, and service options.
• - Experience with large-load or data center interconnection, including phased energization and onsite generation or storage.
• - Knowledge of flexible and non-firm interconnection approaches, including conditional service, curtailment envelopes, and flexible connection agreements.
• - Experience converting distribution connectivity models at scale using CIM, GIS, or vendor exports.
• - Familiarity with AMI interval data, 8760 forecasting, DER hosting capacity, N-1 analysis, and switching studies.
• - Strong Python skills, particularly for profiling numerical code at scale.
• - Experience evaluating or integrating commercial power flow solver SDKs.
• - A background in utility consulting or EPC environments, ideally with exposure to multiple utilities.

Benefits

• - Competitive compensation.
• - Benefits package.
• - Opportunities for professional growth and development.
• - Remote working arrangement based in India.
• - Opportunity to shape how utilities plan and manage distribution grids amid electrification, DER adoption, and increasing data center demand.
• - Work at the intersection of artificial intelligence, data, and power systems engineering.
• - Opportunity to serve as the grid engineering authority for a product that transforms utility data into practical planning decisions.