20 meilleures offres (lead machine learning engineer, ottawa, on) (à pourvoir)

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Amazon Web Services Canada, Inc. —Ottawa, ON
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Lead Product Engineer, Integrations

servicePath
Ontario

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Détails du poste

Temps plein

Profil recherché

ASP.NET Core
React
Salesforce
Coaching
.NET Core
C#
NetSuite
Git
Confluence
Développement dorsal
REST
Télécommunication
React.js
HubSpot
Intelligence artificielle
TypeScript
PowerShell

Description complète du poste

servicePath™ builds quote-to-cash software for IT service providers. Our customers sell multi-year contracts, configured solutions and network circuits, priced to the penny, and that data has to arrive correctly in their CRM and their finance systems. Everything that carries it there is what we mean by integrations, and we are looking for someone to own it.

We are strong proponents of leveraging Artificial Intelligence to drive innovation, aligning with our core value of continuous improvement. By integrating AI into our workflows, we enhance productivity, streamline processes, and elevate our solutions to new heights.

To learn more about our corporate values and how AI shapes our approach, visit our website.

Job Description:

You would own our public API and the developer experience around it, decide what the rest of our integration suite should become, and then build a large part of it. There is usually no specification waiting for you, and writing one is part of the work rather than a prerequisite for starting.

The role exists for the decisions AI cannot make on your behalf. Working out what a customer actually needs when they have described it badly. Choosing between two designs that are both correct, knowing which one survives the next twelve customers. Recognising that a field mapping is technically valid and will still put the wrong number in someone's forecast.

You would set direction with our product manager, and you would be the person the company relies on whenever something crosses a system boundary.

At servicePath™, we seek candidates who are eager to enhance performance by leveraging tools and technologies like AI. Our goal is to streamline tasks, increase efficiency, and maximize productivity, making work more manageable while driving organizational success.

About the Job:

Job Title: Lead Product Engineer, Integrations

Department: Engineering

Reports to: Engineering Director

Shift: Day Shift

Position: Full-time

Location: Canada (Remote)

Travel: Occasional, to client locations

What you would own

The API and the developer experience, first and foremost.

Our public API is how customers, partners and their own developers build on top of us, and it is the centre of this role. We build it code-first: the controllers and view models carry the documentation, the OpenAPI specification is generated from them, and it publishes to our developer site.

You would own the technical roadmap for it working alongside our Product Team. Versioning and deprecation, the design standard and whether it is genuinely followed, and how good the experience is for a developer who has never met us and only has our documentation to work from. Our customer portal, our mobile app and our customers' own developers all read that same API, so a decision about one response shape reaches several consumers at once. This is the part of the job most likely to be judged by someone outside the company.

And the integrations built on it

Connections to customers' CRM and business systems, covering Salesforce, Dynamics, HubSpot and NetSuite: authentication, credentials, field mappings, forecasting rules, reference data synchronisation and connection health. We are replacing bespoke setup work with a configuration surface an administrator can drive, and one customer may run two CRM organisations in different regions, so scoping is part of the design.

Carrier connectivity, where we call eleven carriers live for availability and pricing and turn what comes back into a circuit someone can quote. Each carrier describes bearers, bandwidths and access types in its own way, and most of the work is keeping that normalised when a carrier changes something without telling anyone.

Supplier data ingestion, where vendor catalogues, distributor quotes and rate cards arrive in whatever shape the supplier chose to send. We are moving this onto declarative definitions that AI helps author and the engine then executes predictably, because a wrong mapping damages pricing data quietly.

The problems are commercial before they are technical

Mid-contract upgrades, co-termination, uplifts and escalators, renewals where the deal has changed shape since it was signed, two CRM organisations that disagree about what a customer is called. This is the messy end of quote-to-cash, and it is the interesting part of the job.

You need to understand what a quote, a contract and a renewal mean commercially, well enough to catch a mapping that is correct and still wrong.

How we work

Our work runs through an AI harness. We use Claude Code, doing real work in the codebase, and we will ask you in some detail how you work with these tools and where they let you down.

What you build has to be drivable by an agent as well as a person. In practice that means discrete typed operations instead of one save-everything call, a draft that validates on the server before it commits, a way to simulate what you have authored and see the result, and a single write path shared by the user interface, our in-product AI assistant and any external agent. We design for the agent because it is the least forgiving client we have.

The rest is short. New endpoints are documented where they are written, each product area owns its own API, and behaviour that varies by customer belongs in configuration instead of a bespoke build.

What you need

There is no years-of-experience number on this role, and we are not interested in which frameworks you have been loyal to. What matters is whether you can build at this level without someone breaking the work down for you first.

Required:

C# and ASP.NET Core Web API on modern .NET

OpenAPI 3.0 in a code-first workflow, and REST design where versioning and deprecation are real constraints

OAuth 2.0 and OIDC, token handling and secret storage

At least one major CRM or ERP API integrated in production: Salesforce, Dynamics, HubSpot or NetSuite

Document databases. Ours is RavenDB

React and TypeScript, enough to build the configuration screens for the areas you own

AI tooling as a working habit

Nice to have:

Quote-to-cash, CPQ or billing, where the edge cases are commercial

Telecoms or carrier connectivity

Designing agent or tool interfaces, not only consuming them

Running a public API as a product

Our tooling is VS Code and Claude Code, Git, Jira, Confluence, Storybook and PowerShell.

How you operate

You take something vague and shape it into something real

You simplify a mess instead of adding another layer to it

You think in systems, because one integration decision reaches every downstream consumer

You document as you build, and you treat that as part of the job

You can disagree with a product decision, say why once, and then commit either way

You coach the people around you

What this role is not

Not ticket-driven. Not requirement-led. Not building APIs to someone else's specification. Not documentation-optional. Not architecture-only, because you would be writing code most weeks.

If you prefer clear requirements and predictable work, this is not the right seat.

How we will assess you

We will talk through a messy commercial problem, where what interests us is how you think rather than whether you reach the right answer. We will ask you to build something in front of us using your own tooling, AI included. We will go deep on something you have owned before, pushing on what you decided and what you would do differently. Everyone we interview hears the outcome within 45 days.

Your first six months

We would expect a direction for the API that the rest of engineering can plan against, one customer's CRM integration taken end to end and configured rather than coded, and documentation that somebody else can act on without booking time with you.

If you are an existing employee interested in applying for this role, please submit your resume and reach out to your HR representative for a confidential discussion and guidance on the next steps.

Background Checks and Ethical Conduct:

servicePath™ conducts background checks as part of its hiring process. We take integrity seriously, fraudulent misrepresentation, identity deception, or unauthorized subcontracting will result in withdrawal of an offer or termination.

Equal Opportunity Employer:

At servicePath™, we are proud to be an equal opportunity employer, dedicated to fostering a diverse and inclusive workplace where everyone is valued and respected. We make all employment decisions based on merit, without regard to race, gender, religion, nationality, sexual orientation, disability, or any other protected characteristic. We celebrate and support diversity, recognizing it as a strength that enhances our work environment and drives our success.

Application question(s):

What is your expected Salary in CAD (annually)?
Are you using AI tools in your office tasks? If yes, which tools? Please specify their names.
Are you legally authorized to work in Canada?
What is your current location?
Please provide your updated active LinkedIn Profile link.

Work Location: Remote

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Je souhaite recevoir la dernière alerte emploi pour les postes de ce type : lead machine learning engineer (ottawa, on)

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