Full-time · Calgary-based (hybrid/remote) · Reports to the CPTO

About UsArolytics is on a mission to improve operational efficiency in oil and gas through the lens of strategic emissions management. Our AroIQ platform turns raw SCADA signals into emission event detection, causation analysis and volume quantification for major North American energy companies.

We are growing fast. Several new upstream and midstream customers are onboarding, and the platform is scaling from a handful of sites to hundreds. This is our first dedicated product hire.

How We WorkWe are Rigorous. Our numbers show up in regulatory filings, carbon cost models and operator budgets. Every calculation has to be explainable, reproducible and defensible. We don't ship "close enough."

We are Pragmatic. We work with real industrial telemetry: high-volume, gapped and noisy. A simple product that is right beats a clever one that is almost right. Small team, low bureaucracy, and your work ships fast.

We are Curious. The product sits where process engineering, data science and software meet. We are an AI-native team, and we still build real understanding of the fundamentals underneath. We want people who ask why before they build.

About the RoleYou make sure every number AroIQ shows is right, explainable and in the place people need it.

You own the AroIQ roadmap in execution. You turn product direction into specs and acceptance criteria, accept or reject what the team builds, and run releases with the engineering manager. Most of our product work now lives in the data layer: how model outputs land in the platform, how events, volumes and costs roll up, and how each customer's data maps into one product.

You are the person who looks at a screen or a query result and knows the number is wrong, and why. Product direction, and accountability for it, sits with the CPTO and the executive team. Inside your area you have the authority to decide, and you help shape where the product goes next. You join customer sessions so you hear needs first-hand. You write specs and acceptance criteria with Claude and own the judgement on top.

What You DecideYou have real authority in your area. Direction is shared; the calls inside your area are yours.

- You decide: what ships after acceptance testing, scope and sequencing within the quarter, what each field in the data contract means, and whether a customer's onboarded data is accepted
- You shape with us: product direction and the themes on the roadmap
- You bring to us: new commitments to customers and changes of direction

How You'll Work: AI-Augmented ProductThis is an AI-augmented product role. Claude does the volume, you do the judgement.



Our product work already runs this way:

- Customer calls become structured signal. Agents process call transcripts into feature requests, decisions and customer notes, so nothing evaporates.
- Specs start as drafts, not blank pages. PRDs, technical designs and build prompts are drafted by agents from the evidence, then shaped and decided by a person.
- Prototypes before tickets. We build working prototypes on real customer data, inside our access controls, and hand them to engineering instead of describing screens in words.
- Purpose-built tools in an hour. A one-off labelling tool for an analyst, a parameter tuner, an export check. Built, used and thrown away.
- Data QA at scale. Claude profiles a new customer export, flags what won't map and drafts the transform. You decide what is right.

You will extend this. You'll build and maintain your own agents and skills, and you'll know where Claude is reliable and where it needs an expert to check it. Acceptance stays human: you own whether the data shows up right. Customer data stays inside our approved environments and access controls, and every prototype, agent and AI tool works within them.

What You'll Do

Own delivery

- Run the roadmap backlog with the engineering manager: sequence, scope and cut
- Write the spec and acceptance criteria for every build, each with a real data example and the expected values
- Run user acceptance testing and decide what ships
- Write release notes the customer-facing team can use

Own data accuracy

- Keep reference datasets with known-correct totals for each customer, and the regression checks that run against them
- Own the data contract at every boundary: customer systems into our data platform, data science outputs into AroIQ, and AroIQ back out to customers. What each field means, not just where it goes
- Accept each new customer's data onboarding. Data Engineering builds the pipeline; you decide whether the data is right: mapping, completeness, and numbers that reconcile
- Specify the logic behind emissions, volumes, KPIs and costs so every figure is reproducible and auditable

Work with customers and the team

- Join customer sessions, capture feedback and turn it into scoped work
- Work daily with data scientists, data engineers and emissions analysts




- Keep the product simple: push back on scope that adds screens without adding value

What We're Looking ForRequired

- Several years (typically 4+) in B2B Enterprise/SaaS product management, technical product or data roles on data-heavy software
- Technical awareness, no software engineering background needed. You understand how data flows from source to screen, what a data contract guarantees, and at what grain a number is counted. You can read an export, sanity-check a query (yours or Claude's) and reconcile numbers across sources. Writing SQL by hand is not required
- Domain experience in oil and gas, emissions or industrial operations: SCADA or process data, GHG quantification, or emissions reporting
- A track record of acceptance criteria engineers build from without rework
- Fluent with AI-assisted work (Claude or similar) for specs, analysis and QA, and able to judge its output
- Transparent writing. You can explain a number to an operator and to an engineer

Preferred

- A background as a process, facilities or emissions engineer who moved into software or product
- Working knowledge of methane regulation and reporting frameworks in Canada and the US
- Experience with PostgreSQL, time-series data or data pipelines
- Time at an early-stage company

Where the Work Is GoingThe problems open now or on the near horizon, yours to shape:

- Scaling from a handful of sites to hundreds per customer, with numbers that stay consistent across every view
- One product serving both emissions and operations use cases, without forking the data model
- Moving from historical data drops to near-live data from customer systems
- Confidence and uncertainty shown per event, kept separate for detection, causation and quantification
- A data contract that holds as the number of customers grows

What You Aren't

- A UI-first product manager whose main output is wireframes
- Someone who needs another person to check the numbers
- A project manager who tracks tickets for others
- Someone who hands acceptance to a tool without owning the result
- Someone who needs big-company structure, layers of sign-off and someone else deciding what matters
- Someone who uses AI as a chat box for the occasional question, rather than as the way the work gets done

What We Offer

- Competitive salary and comprehensive benefits
- Direct ownership of a product used by major North American energy companies
- Daily work with data scientists and emissions specialists who know the domain deeply
- A small team where your decisions ship in weeks, not quarters
- Calgary-based, with hybrid and remote flexibility

📌 Product Manager, AroIQ (Calgary)
🏢 Arolytics
📍 Calgary