Forward Deployed Engineer

๐Ÿข SensorUp Inc. ยท all SensorUp Inc. jobs
๐Ÿ“ Canada
๐Ÿ’ฐ CAD 120,000 - 150,000 / annual
๐Ÿ“… Posted 2026-09-06 ยท via Himalayas
๐Ÿท Forward-Deployed-Engineer,Solutions-Engineering,Technical-Consulting,Data-Engineering,Product-Engineering,Mid-Level-Forward-Deployed-Engineer
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Who We Are

SensorUp is a purpose-built integrated platform to connect field operations and corporate reporting across the full emissions management lifecycle, from field inspections and leak detection through repair verification, regulatory and voluntary reporting, continuous improvement, and audit. We work with some of the world's leading upstream and midstream methane operators, and we're at an inflection point: growing our enterprise customer base, deepening strategic partner relationships, and building toward a future where AI-assisted emissions management is the norm, not the exception.

We're a focused, cross-functional team distributed across Canada and the United States, moving fast and motivated by the problem we're solving. We believe that eliminating fugitive methane emissions is both an environmental imperative and a solvable operational challenge, and we build our platform accordingly.
Our Vision

We're building the infrastructure layer for how the energy industry measures, manages, and monetizes emissions, from LDAR programs and OGMP 2.0 certification to carbon credit markets. Our goal is a world where every methane molecule is accounted for, and every operator has the tools to act on that data in real time.
The Role

The fastest way to show an operator what SensorUp Studio can do is to build their workflow in front of them. We are standing up a workshop motion for new enterprise prospects: a working session with an operator's methane and operations team that ends with a real slice of their workflow composed live in Studio, on their data. This role is the build seat in that room. You will take a prospect's messy asset registries, detection feeds, and reporting pain, and turn them into something running before the session ends. Then you will generalize what you built into our Solutions Library, so every workshop makes the platform stronger and the next deal faster.
Your Impact

What is different at SensorUp 12 months from now because you were here:

- Own the build seat in our prospect workshops end to end: prepare the environment from intake, compose live in Studio during the session, and deliver the readout that carries the deal forward

- Turn every workshop build into a generalized, reusable entry in the Solutions Library, so composed workflows compound into product rather than one-off demos

- Cut the time from a prospect's raw data drop to a working demo environment from weeks to days, including large asset registry and observation loads

- Build the reference implementations of core detect, evaluate, action, and record workflows that sales and delivery reuse across accounts

- Feed field-observed platform gaps back to product and engineering with enough specificity that they land on the roadmap

Your Experience
Must-Haves:

- You have shipped production software or data pipelines yourself, recently and hands on. Strong SQL and working Python

- You have worked with messy operational data: asset hierarchies, sensor and observation records, exports that do not agree with each other

- You have built in a customer-facing setting before: implementation, solutions engineering, consulting delivery, or forward-deployed work

- You are comfortable composing a solution live, with incomplete requirements and an audience watching

- You can explain a technical decision to a non-technical operator audience without jargon

Nice-to-Haves:

- Oil and gas, emissions, or adjacent heavy industry experience

- Familiarity with geospatial, IoT, or time-series data

- Experience building on configurable or low-code platforms (Palantir Foundry, Retool, or similar)

- Early-stage startup experience where you owned outcomes end to end

Who You Are

You're energized by hard problems in complex environments, the kind where the data is messy, the stakes are real, and the solution actually matters. You don't need perfect conditions to do great work; you build clarity out of ambiguity and move fast without cutting corners.

You

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