Implementation Consultant - Service

Gigawatt

23d

About The Position

Gigawatt is building an AI-native field service platform for utilities. The Implementation Consultant - Service configures each utility’s work types, crews, territories, and business rules into a live, validated Service module configuration that dispatchers and crews can trust. This is a hands-on configuration role with analytical depth, using an AI-accelerated configuration workflow rather than configuring everything manually. It is neither a software-engineering nor a pure business-analysis role. The consultant owns configuration units from requirements through validated sign-off, including intake, analysis, configuration guidance, dependency-ordered setup, validation against real crew-days, sign-off, and promotion. The role translates utility work and legacy systems into platform models, tunes scheduling and exception rules, and helps establish a reusable configuration standard across operating companies. The consultant partners with Product and engineering on fit-gap, validates schedules with dispatchers before go-live, triages production issues through the promotion process, and serves as the client’s day-to-day contact and first line of defect intake. The role is based in the United States, in any time zone, and requires the ability to travel to client sites. The consultant will configure field service for a major U.S. utility as part of a lean, senior, AI-accelerated team.

Requirements

At least 7 years of experience in field service management, configuring, implementing, or consulting on FSM software for enterprise customers.
Hands-on declarative configuration experience with an FSM platform such as IFS Field Service Management, ClickSoftware / Salesforce Field Service, Oracle Field Service, ServiceNow Field Service Management, SAP Field Service Management, or a similar platform.
Experience configuring work types, resources and skills, territories, calendars, and scheduling policies or optimization rules.
Understanding of how scheduling constraints, priorities, SLAs, and travel shape an optimized schedule and why dispatchers override it.
Experience leading requirements workshops with operations and dispatch stakeholders and taking configuration through testing, UAT, and go-live on at least one enterprise rollout.
Experience mapping and migrating data from a legacy field-service or work-management system, including parallel runs and cutover.
Experience helping field organizations adopt a new way of working and comfort working with supervisors, crew leads, and labor stakeholders.
Analytical ability to interpret operating procedures or work-order histories and identify underlying rules and data models.
Comfort working with structured data and spreadsheets and alongside AI tooling.
Based in the United States and able to travel to client sites.

Nice To Haves

Experience with utility field operations, including distribution and transmission crews, meter and service orders, storm restoration, and inspection programs.
Experience migrating a customer off a legacy field-service or work-management system.
Experience with mobile workforce rollouts, including offline-capable field apps, digital forms, and safety briefings.
Exposure to integrations with asset management systems such as Maximo, GIS systems such as Esri ArcGIS, outage management systems, and inventory systems.
Exposure to AI-accelerated or human-in-the-loop configuration workflows.
A preference for building reusable components instead of one-off solutions.

Responsibilities

Configure the Service module end to end, taking each configuration unit from intake and analysis through configuration, validation against real crew-days, sign-off, and promotion.
Map utility work categories and legacy order types to ticket types, durations, required skills, priorities, and SLAs across customer and meter work, maintenance and inspections, projects and new construction, and emergency restoration.
Convert legacy territories, routing tables, and cross-references into dispatch areas and constraints; set KPI weights and explain differences between legacy-system output and the optimization engine to the client’s operations team.
Tune named exception queues and rules so work the scheduler cannot place is surfaced with a reason and fewer tickets require dispatcher intervention.
Model scheduling constraints, including skill and certification grades, crew composition, territory boundaries, appointment windows, site access, permits and keys, parts and equipment, and work rules such as hours of service.
Assess hand-coded legacy rules against the form builder and rules engine, retire workarounds, escalate genuine gaps as product requirements, and use online validation where appropriate.
Establish and maintain a best-practice configuration standard across operating companies, representing justified differences as configuration rather than forks.
Lead the operational change to engine-driven service and act as the day-to-day face of the change for field organizations.
Run the AI-assisted configuration flywheel and partner with Product and engineering on fit-gap.
Validate schedules against dispatcher expectations before go-live, triage production issues through the promotion process, and serve as the client’s day-to-day point of contact and first line of defect intake.
Develop reusable configuration templates for ticket types, crew models, and calendars.