About Owlery

Owlery is an AI-powered logistics platform built for shippers — the brands, manufacturers, and logistics teams whose product is actually moving. We're two things in one: a TMS that runs freight operations end-to-end, and an AI Logistics Teammate that actively manages those operations — resolving exceptions, communicating with carriers, and optimizing decisions around the clock. We replace both the spreadsheets and the manual work that still dominate the industry.

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We were founded in 2022 by principal engineers from Uber Freight, and we're backed by institutional investors. Owlery is growing fast (>4x year over year) with a small team that punches well above its weight. We're remote-friendly with offices in the San Francisco Bay Area.

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The Opportunity

You will own the customer-facing support and service of a product that powers live logistics operations. When something looks wrong to a customer, the answer is almost never on the surface. It could be an integration that silently stopped returning data, a stale configuration, a carrier API behaving badly, a prompt that steered the agent somewhere unhelpful, or the Teammate making a decision that was correct and looked wrong. Some of those you fix. Some of those you explain. Telling which is which, quickly, is the core skill of this job.

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We're making our first dedicated hire to own this scope of work. You'll be the person who interfaces with our customers and their partners to make sure Owlery is driving the full value they expect. You will have the access — including to the codebase — and the authority to fix most of them yourself. Your judgment determines what gets fixed now, what gets escalated, and what goes on the roadmap.

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On the title: "Engineer" is here because the work is technical and you'll spend real time in logs, dashboards, admin consoles, and the codebase. You'll have repo access from your first week. When a customer issue traces back to a bug, the default is that you fix it — not a whole new feature, but the broken query, the unhandled edge case, the field mapping that silently drops data. Your backlog is customer-originated rather than sprint-originated. If you want to spend most of your week building new product, this isn't your role. If you want to diagnose hard problems in a live system and ship the fix the same day instead of waiting for a planning cycle, keep reading.

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This is our first dedicated hire for this scope, and it's the role we build our support and CSM function around. You'll work alongside our Customer Success Manager, who owns account strategy, renewals, and QBRs.

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We are a startup. This is a build-it role. Nobody is going to hand you a runbook. You get to write the first one.

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What You'll Do

• Inbound support, end to end. Email, Slack, Teams, and whatever other door customers knock on. You resolve the large majority yourself rather than routing it onward.
• Diagnosis. Trace an integration failure, read logs and dashboards, follow a load through the system, and determine whether the platform is wrong or the input was. Reproduce before you escalate.‍
• Direct fixes, including in code. Correct customer integrations and system configurations through internal tooling, carefully, with a trail of what changed and why. Adjust prompts on internal and customer-facing agents when that's the actual root cause. And when the root cause is a bug, fix the bug — you'll open the PR yourself rather than file a ticket and wait for someone else's sprint. Escalate what needs architectural judgment, not what's merely tedious.‍
• Explaining the Teammate. Tell customers why the agent did what it did, in language that builds trust rather than eroding it. This is harder and more valuable than it sounds, and it's the part of this job you won't find anywhere else.‍
• Incident communication. When something breaks, you own scope, impact, and status - delivered while the fix is still in flight, not after.‍
• Product influence. You'll see every issue across every customer, which makes you the best-informed person in the company on what's actually broken. Bring that to the roadmap with evidence, not anecdotes.‍
• Building the function. Establish the escalation path to engineering. Define our first support metrics - response time, first-contact resolution, backlog health. Build the knowledge base. Most importantly: make as much of this self-service as possible, so the second and third hires onto this team have leverage instead of a bigger queue.

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Reactive work always feels more urgent than proactive work, and at most companies that means the proactive half quietly never happens. We expect you to be proactive in customer outreach, product feedback, developing documentation, and shaping our roadmap. We will carve out time to ensure reactive work does not get in the way of driving business value.

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What Success Looks Like

First 90 days. You're handling the majority of inbound without pulling engineers in. You've shipped your first bug fixes without an engineer walking you through the codebase. You've documented the ten most common issues and how to resolve them. You can explain any Teammate decision to a customer without checking with anyone.

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Six months. There's a real escalation path with defined severity levels. Customer-reported bugs are routinely closed by you; engineering sees the ones that genuinely need them. First-contact resolution is measured and improving. The knowledge base covers enough that a meaningful share of inbound never reaches you.

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Twelve months. Ticket volume per customer is flat or falling while customer count grows. You have a defensible point of view on what to hire next and how the function should be structured. You're influencing the roadmap on product-quality issues before customers hit them.

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Who You Are

• At least 2-4 years in technical support, customer or solutions engineering, or a hands-on engineering role with real customer contact, at a B2B SaaS company. We care more about what you've debugged than what your title said.
• You can fix a bug in code. Not build features — fix bugs. You can find your way around an unfamiliar codebase, isolate what's actually wrong, write the fix and a test for it, and get a PR reviewed and shipped. Python or JavaScript, plus enough SQL or Mongo to answer your own data questions.
• You understand REST APIs — payloads, auth, error responses — and can work out whether an integration is failing on our side or theirs.
• You know how to change LLM prompts to get the results you need. The AI Teammate we're building for our customers is not the only agent in our stack. You'll be using, changing, and enhancing both internal and external AI agents on a regular basis.
• You've used observability or analytics tooling (Datadog, Grafana, Sentry, Cloudwatch) to investigate a live issue, and you're at home in an internal admin console.
• Fluent, professional English, written and spoken. Our customers are North American logistics teams, and you'll be writing to them all day and on calls with them regularly. Clear, calm, and specific under time pressure — especially when the customer is none of those things.
• You have judgment about escalation. You know the difference between a problem worth two more hours of your own time and one that needs an engineer right now.‍
• You want to build a function, not join one. We are a small, nimble, and mighty team. You will have real ownership and no bureaucracy. Some people love that; it's worth knowing which you are before you apply.

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Nice to Have

• Experience in our stack: TypeScript / MongoDB. Not required, but it shortens your ramp considerably.
• Logistics, freight, telematics, or supply chain experience. Think TMS, EDI, or API-based carrier integrations.
• You've stood up a knowledge base or a support process from scratch and have real opinions about how to actually deflect tickets.
• Comfort with light scripting (Python, JavaScript) and querying (SQL or Mongo) for bulk fixes and data pulls.
• Experience supporting an AI or automation product, where "why did it do that" is a routine question.

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What You'll Get

• Competitive salary benchmarked to your local market.
• Access to premium AI tools including Claude Pro, plus the internal AI agents already running large parts of our operation.
• Periodic travel to get the remote team together face to face.
• Benefits vary by location.