About Gridware
Gridware is a San Francisco-based technology company dedicated to protecting and enhancing the electrical grid. We pioneered a groundbreaking new class of grid management called active grid response (AGR), focused on monitoring the electrical, physical, and environmental aspects of the grid that affect reliability and safety. Gridware’s advanced Active Grid Response platform uses high-precision sensors to detect potential issues early, enabling proactive maintenance and fault mitigation. This comprehensive approach helps improve safety, reduce outages, and ensure the grid operates efficiently. The company is backed by climate-tech and Silicon Valley investors. For more information, please visit www.Gridware.io.
Role Description
This is Gridware's first dedicated design research role, and it is a foundational hire for our product organization.
You will join a product designer and work in close partnership with product managers across multiple lanes. Your job is not to produce one-off research deliverables, but to build the research infrastructure that helps the entire team make better product decisions, faster.
But this role is more than a UX researcher who runs studies and draws journey maps. The core question this role exists to answer is: how do utility customers move from signal to evidence to decision to action — and what does Gridware need to build, surface, and externalize to support that chain reliably?
The team needs someone who can map how utility customers move from signal → evidence → decision → action, and then help us externalize that reasoning inside the product. Our users are domain experts making high-consequence decisions: operators, wildfire mitigation managers, vegetation managers, asset engineers, field crews, program owners, and executives. Each role has different decision rights, evidence needs, trust thresholds, failure modes, and reporting obligations. Understanding that decision landscape — the who, the goals, the motivations, and the value — is the heart of the job.
You will need to move fluently between generative research and service design thinking. Running rigorous qualitative studies with expert users, while also mapping the systemic journeys that cut across product lanes and organizational boundaries will help keep the cross-functional teams grounded in what customers actually understand, decide, and do.
Responsibilities
Build decision-centered customer profiles. Go beyond personas. Build profiles mapped to the actual decisions each utility role makes: what they decide, what evidence they need, which systems they trust, what actions they're authorized to take, and what happens when the product is wrong or unclear. These profiles ground product direction in operational reality, not demographics
Map service design across the utility operating model. Create the journey maps and service blueprints that span end-to-end utility workflows — hazard prevention strategies, grid monitoring, vegetation management, field response, escalation, reporting, and post-event review. Capture frontstage user actions alongside backstage Gridware processes, data dependencies, integrations, and handoffs. These artifacts show how users experience our products as one system, where the experience breaks down, where internal processes create friction, and where automation changes the human role. They are shared design infrastructure, not one-team documents
Lead GIS and data-rich workflow research. Study how expert users interpret maps, asset topology, imagery, weather and vegetation layers, telemetry, anomaly detection, confidence scores, and model-generated recommendations. You don't need to be a GIS analyst, but you need to be fluent enough to research spatial and data-heavy workflows without oversimplifying them, and understand: what users see, what they trust, where they are confused, and what the product must do to make complex multi-layer data legible and actionable
Make system reasoning legible. When Gridware surfaces a risk score, anomaly, recommended action, or priority area, users need to understand why. Help define what the product must externalize — source provenance, data freshness, confidence and uncertainty, risk drivers, recommended action, and consequence of inaction — so users can trust, challenge, explain, and act on the system's output
Study trust in automation and AI-assisted decisions. Investigate how expert users calibrate trust in automated recommendations: what evidence is enough to dispatch a crew, prioritize vegetation work, escalate an alert, or defer action? Where do users need override paths? What makes a recommendation credible in a high-consequence utility context? As workflows shift from manual execution toward automation, exception handling, and supervised intervention, this becomes a product and systems problem that research must inform
Build an evidence architecture. Research outputs shouldn't live as scattered notes. Establish systems that make research reusable and compounding — connecting customer profile, workflow, decision, data source, product surface, failure mode, required evidence, design implication, product decision, and open questions. This becomes the foundation for how product, design, and cross-functional partners make decisions across roadmap cycles
Bring research into product planning. Work with product managers to embed research into roadmap cycles — ensuring outcome statements are grounded in user evidence, that problem spaces are defined before solutions, and that teams have the user context they need to prioritize well
Establish a shared vocabulary for Gridware's users. Operational evidence about who these people are, what they know, what they need to see in order to act, and what the cost of failure is in their context — not marketing personas
Facilitate cross-functional research and alignment. Run workshops that bring product, engineering, GTM, and support into shared understanding of user problems. Help internal teams see the product through users' eyes, and ensure insights don't stay trapped in the design org
Required Skills
Research rigor with systems and descision-mapping thinking. Deep command of qualitative methods — interviews, contextual inquiry, usability testing, diary studies, workflow observation — applied with rigor, not ritual. You move fluidly from an individual user's experience to a service blueprint showing how the whole organization supports or undermines that experience
Experience with expert users and technical domains. You're comfortable designing research with people who know more about their domain than you do. You can extract tacit knowledge from expert practitioners, and you don't need a product to be simple before you can research it
High-stakes operational context fluency. You understand that when decisions carry real operational consequences, the research bar is higher. You can study consequential workflows without distorting them, and translate findings into product implications teams can act on — without oversimplifying the risk context
Decision and service design literacy. You can produce a service blueprint and know how it differs from a journey map and when each is the right tool. You can facilitate a multi-stakeholder journey mapping workshop and turn the output into something product teams can actually use. You think natively in terms of decisions, evidence, and consequence
Infrastructure builder, not just study runner. You've created research practices from scratch — the systems, templates, and repositories that make research institutional rather than ephemeral. You treat research output as product infrastructure
Strong synthesis and communication. You move from raw data to structured insights to clear product implications without losing nuance. You write well. You can present to a leadership audience in a way that makes implications concrete and tradeoffs visible
Autonomous and founding-team oriented. This is the first research role at Gridware. You're building the practice, not inheriting it — comfortable with ambiguity, resourceful, and energized by defining what research looks like at a company rather than fitting into an existing model
Bonus Skills
Background in infrastructure, energy, utilities, IoT, field operations, or similarly complex technical environments
Experience researching products that involve automation, exception handling, or human-in-the-loop systems
Fluency researching GIS, geospatial, or other data-rich expert workflows
Familiarity with contributing to or shaping design system foundations
Experience working across internal operations tools and customer-facing products simultaneously