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Canada
Remote only
Hi, I'm Akbay, Head of Engineering at Reflow.
Most engineering roles at this stage ask you to execute. Pick up tickets, ship features, move to the next one. That's not what we're looking for.
Reflow is building something that requires you to care about the outcome, not just the output. We track how work actually happens inside organizations and turn that into intelligence. The data is messy, the product surface is wide, and the problems are greenfield. You need to want to dig into that, not just be okay with it.
I'm looking for someone who gets energy from complexity, moves fast without cutting corners on the things that matter, and wants to see their fingerprints on a product that real teams depend on. Someone who can build and lead, in that order.
If that sounds like the kind of work you want to be doing, read on.
Akbay
Most organizations have no reliable way to understand how work actually gets done. They track outputs, not workflows. They measure activity, not intelligence. The result is a massive blind spot at the operational layer of every team.
Reflow closes that gap. We're a workforce and workflow intelligence platform that integrates with the tools teams already use, detects how work flows through an organization, and surfaces the insights and automation that help teams improve. We're early, growing fast, and moving into the next wave of intelligence-driven capabilities.
Month 1: Get into the product. Learn the codebase, understand the data model, and ship something real. You don't need to know everything on day one, but you should be delivering working, clean code fast enough that the team feels the lift. Expect to spend the majority of your time building.
Month 2: Own a surface. Take end-to-end ownership of a meaningful feature or system, from API design through to the frontend. Start developing strong opinions about how things should be built and why. Begin getting to know the team closely, how they work, what they're good at, and where they need support.
Month 3: Start leading. Move from knowing the team to actively making them better. Run regular 1:1s, give direct feedback, and start removing the things that slow people down. You are still building, but now you are also making it easier for everyone else to build well.
You stay hands-on; that's non-negotiable. But the balance shifts. Over time, roughly 70% of your time goes to building and technical decision-making, and 30% to the team, hiring, 1:1s, performance conversations, and raising the bar on how we work.
You are not a manager who used to code. You are an engineer who also leads.
Example projects on the horizon:
Build and scale analytics dashboards that make complex workflow data fast, visual, and actionable.
Own API design and optimization between our apps and backend services as usage grows.
Help shape the backend architecture for our next generation of AI-driven and automation-based features.
Push frontend performance and UI quality as we land larger, more demanding customers.
Run technical interviews and help build a hiring process that consistently finds great engineers.
Some leads think leading means reviewing PRs and running standups. That's not what we need.
When something is moving slowly, we want someone who asks: "Who on the team has the most context on this? What's actually blocking them?" They reach for people and their capabilities, not process and documentation. They know what each engineer is good at, what they're struggling with, and how to get the best out of them today, not after implementing a framework.
At this stage, the best thing a lead can do is make everyone around them faster, clearer, and more confident by being the strongest technical voice in the room and the person people most want feedback from.
High trust, high speed. We don't manage output through meetings or status updates. You'll know what matters, and you'll have the autonomy to go build it.
Data is the product. We work with large, complex workflow datasets. Performance, reliability, and data integrity aren't afterthoughts; they're core to what we ship.
AI is part of the craft. We use AI tooling actively across the engineering workflow. We expect you to have opinions about what works, experiment openly, and bring the team along.
Direct collaboration. You'll work closely with product, design, and data. No long handoff chains. The people building the feature are usually the people closest to the problem.
This role is for you if:
You are comfortable moving between backend and frontend.
You were a strong IC before you started leading, and you didn't stop being one.
You have built analytics-heavy applications before and you know what it takes to make data fast, usable, and visual.
You are pragmatic about shipping but opinionated about quality, and you know when each one matters more.
You have worked in an early-stage environment where the playbook didn't exist and you had to figure it out.
You are actively using AI coding tools in real production work and have opinions about how they change the workflow.
You are comfortable having hard conversations about performance, directly and constructively.
You want to work closely with the founding team and have your decisions actually matter.
This role is probably not for you if:
You chose engineering leadership because you wanted to stop coding.
You need well-defined specs and stable requirements to do your best work.
You think of frontend and backend as separate jobs that different people should own.
When something goes wrong, your first instinct is to create a better process rather than get the right person on it.
You want a large team, an established process, and a clear career ladder from day one.
You haven't touched production code recently and are looking to ease back in gradually.
Required
8+ years of backend and frontend engineering experience, with a track record of owning complex systems end-to-end.
Strong hands-on experience with Django (Python) and Next.js (React), production systems, not side projects.
Some engineering leadership experience: 1:1s, hiring, code reviews, mentorship. Ideally at a similarly staged company.
Solid understanding of API architecture, data modeling, and query optimization.
Proven experience building analytics-heavy applications, dashboards, data visualizations, and real-time reporting.
Comfortable owning the full cycle from schema design to shipped UI.
Hands-on experience with AI-assisted coding tools in real production work.
Strong written communication; we're distributed, and context needs to travel well in writing.
Open to working across time zones with a globally distributed team.
Familiarity with data warehousing, ETL, or analytics pipeline concepts.
Experience with frontend performance optimization and responsive UI design.
Exposure to AI-driven or automation-based backend systems.
Experience designing technical interviews or building hiring processes from scratch.
Previous experience at a fully remote company.
High autonomy and direct impact on product architecture and team culture from day one.
Work directly with the founding team; your decisions will be visible, and they'll matter.
Fully remote, work from wherever you do your best work.
A genuinely hard problem at the intersection of data, intelligence, and product.
We offer competitive pay based on the market and where you’re located. The salary ranges in our job postings are intentionally wide because they need to cover both U.S. and international candidates. Our final offer will depend on things like your experience, skill set, and location.