[All remote jobs](https://jobicy.com/jobs.md)[![Workleap logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/b84329e1-221.png)](https://jobicy.com/company/workleap.md)[Workleap](https://jobicy.com/company/workleap.md) # Senior AI Developer, Data AI Summary Workleap is hiring a Senior AI Developer to productionize AI systems and agentic workflows for its products and internal operations. The role combines Python and SQL engineering with foundation models, governed-data integrations, evaluation, observability, security, and cost management. The developer will set reusable engineering patterns and influence architecture across a shared Data team. Close collaboration with data scientists, software engineers, product teams, platform specialists, and security partners is central to the role. This is a remote Canada-based position with optional access to the Montreal office.[Apply for this job](#job-application)[View company](https://jobicy.com/company/workleap.md)ShareRemote from[Canada](https://jobicy.com/job-region/canada.md)SalaryCAD 140k–170k / yrDepartment[Software Engineering](https://jobicy.com/categories/engineering.md)EmploymentFull TimeExperienceSeniorPublished12 Nov 2026Apply before12 Dec 2026Listing views50Application actions2Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. Opportunity details ## About this role. ### Company Description [Workleap](https://jobicy.com/company/workleap.md) is a Montreal-based tech company, founded in 2006. We’re builders at heart, we make simple products that actually matter to the people who use them. We have two product lines: [Workleap Agent](https://workleap.com/), our newest solution built to make every manager more effective, and [ShareGate](https://sharegate.com/), the world’s leading solution for Microsoft 365 migration and governance. More than 15,000 companies worldwide trust us to do exactly that. We’re intentional about who joins us. If you’re the kind of person who gets excited by a hard problem and wants to help shape what comes next, there’s a place for you here. ### Your role At Workleap, turning AI experiments into production capabilities is already part of how we build products and improve internal operations. Our Data team brings strong data engineering and science foundations; this role adds dedicated production AI engineering. As a Senior AI Developer, you’ll design, build, and operate the AI systems and agentic workflows that connect foundation models to our data, tools, and applications, and you’ll set the technical direction for how we do it well. Your impact: * Ship production AI systems and agentic workflows that deliver measurable value in Workleap’s products and internal operations. * Own the production quality of those systems: observability, testing, security, and cost built in from the start. * Turn evaluation evidence from Data Scientists into engineering improvements, so we know whether a system is getting better or worse. * Engineer the context integrations that let agents use governed data and application capabilities accurately. * Define reusable patterns and components so the next team starts from a working foundation, not a blank page. * Drive architecture decisions across quality, risk, and cost, and make the trade-offs explicit. ### Your team You’ll join Workleap’s Shared Tech – Data team, a hands-on team of six Data Engineers and Data Scientists responsible for the data and AI foundations supporting our products and internal teams. We value technical judgment, pragmatism, simplicity, autonomy, collaboration, and reliable delivery. You’ll work closely with both disciplines and partner with Software Engineers, Product teams, and Platform and Security specialists to bring AI capabilities into production. Over the next 6-12 months, you’ll work on questions like: how does someone ask an analytical question of governed data and get an answer they can trust? How do we know an AI agent is good enough to take on more responsibility? How do we run AI features with the same rigor as any other critical system? Our technology ecosystem includes Python, SQL, Snowflake (Cortex, Cortex Agents, Cortex Code), Claude, OpenAI, Braintrust, OpenTelemetry, Terraform, and GitHub. ### What you’ll bring * Strong production engineering in Python and SQL, with testing, CI/CD, and experience operating cloud systems; * Hands-on experience building and operating AI applications with foundation models, agents, tools, and context; * Experience instrumenting and evaluating non-deterministic systems: observability, evals, regression testing; * Sound architectural judgment across reliability, security, and cost, and the confidence to form and defend a technical opinion; * Experience building components or tooling that other developers adopt; * Working knowledge of Snowflake and its AI capabilities (Cortex), or the ability to ramp up on them quickly; * A builder mindset: you own what you ship, experiment quickly, and use AI-assisted development tools daily and critically; * Bonus: AI services on Azure, AWS, or GCP, or developer platforms that accelerate AI adoption across teams. Most of this sounds like you? Apply. ### What the job comes with * Base salary: $140 000 – $170 000. This range reflects our Canada-wide compensation scale. Final offers may be adjusted based on the candidate’s region to align with local market conditions. * Annual bonus program. * LTIP program, share in Workleap’s long-term growth. * RRSP + Family health insurance + telemedicine + annual wellness budget. * Flexible vacation policy. * Remote work, with access to our Montreal office. * In-person gatherings twice a year. * Claude access, for everyone. ### What drives us At Workleap, we build software that sits at the center of how people experience work, every day, at every level. We move fast. Priorities shift, decisions get made with the information we have, and we iterate. If you thrive on intensity and ambiguity doesn’t slow you down, you’ll feel right at home. We’re builders. We do what it takes to move forward. AI is part of our toolkit. We use it to go faster and decide smarter, not to replace judgment. If you want real impact and a place where your decisions matter, this is it. ### How we hire Transparency is how we hire — for you as much as for us. Here’s how it works: a first call with a recruiter, then a virtual interview with the hiring manager. You’ll then complete a take-home case study, followed by a meet with future colleagues to discuss it together. Depending on the role, the process may vary slightly — your recruiter will walk you through it on your first call. We use AI to support certain steps of the process, but every hiring decision remains human. We can’t wait to meet you. By applying, you confirm that you have read and agree to our [privacy policy](https://workleap.com/trust-center/privacy). #LI-Remote Show more [Apply now >](https://jobicy.com/jobs/161590-senior-ai-developer-data.md) * ![Upload CV](data:image/svg+xml;base64,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) ### Upload your resume now To unlock remote work opportunities and be discovered by global employers. This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThis is a senior production AI engineering role requiring strong judgment across non-deterministic systems, cloud operations, reliability, security, evaluation, and cost. The candidate must independently establish technical direction while delivering reusable systems in a fast-moving environment. ## Salary analysis Estimated compensation compared with the broader CA market for similar roles. Estimated job median (per year)Market rateC$155,000CA market range (per year)C$145k–C$185k0C$203.50k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer discloses a base salary range of CAD 140,000 to CAD 170,000. The annual cadence is inferred from the full-time senior role and the magnitude of the Canada-wide base salary range; the posting does not explicitly state a pay period. The estimated Canadian market range for a senior production AI engineering role is CAD 145,000 to CAD 185,000 per year. ## Core skills Skills and capabilities most closely associated with this opportunity. [Python](https://jobicy.com/jobs?search_keywords=Python.md)[SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[AI engineering](https://jobicy.com/jobs?search_keywords=AI%20engineering.md)[Agentic workflows](https://jobicy.com/jobs?search_keywords=Agentic%20workflows.md)[Foundation models](https://jobicy.com/jobs?search_keywords=Foundation%20models.md)[LLM evaluation](https://jobicy.com/jobs?search_keywords=LLM%20evaluation.md)[Observability](https://jobicy.com/jobs?search_keywords=Observability.md)[OpenTelemetry](https://jobicy.com/jobs?search_keywords=OpenTelemetry.md)[Snowflake Cortex](https://jobicy.com/jobs?search_keywords=Snowflake%20Cortex.md)[Cloud systems](https://jobicy.com/jobs?search_keywords=Cloud%20systems.md)[CI/CD](https://jobicy.com/jobs?search_keywords=CICD.md)[Terraform](https://jobicy.com/jobs?search_keywords=Terraform.md)[Security engineering](https://jobicy.com/jobs?search_keywords=Security%20engineering.md)[Software architecture](https://jobicy.com/jobs?search_keywords=Software%20architecture.md)[GitHub](https://jobicy.com/jobs?search_keywords=GitHub.md) Sample interview questionsHow would you move an AI agent from prototype to a reliable production service?I would begin with a narrow, measurable use case and define quality, latency, reliability, security, and cost targets. I would build a versioned evaluation suite, add tracing and structured telemetry, implement regression tests and guardrails, and use staged releases with monitoring and rollback criteria. How do you evaluate a non-deterministic AI system? I combine automated task-specific metrics with curated human review for high-risk or ambiguous outputs. I version prompts, tools, models, and datasets, run regression evaluations before releases, analyze failures by category, and monitor live production outcomes to identify drift. What considerations matter when connecting an AI agent to governed enterprise data? The agent should use least-privilege access, respect row- and column-level controls, retrieve grounded context from trusted sources, and preserve audit trails. I would also validate tool inputs and outputs, minimize sensitive data in prompts, and clearly communicate uncertainty or unsupported answers. How would you balance AI quality, latency, and operating cost? I would make the trade-offs explicit through service-level objectives and cost telemetry. Techniques include model routing, caching, context optimization, batching where appropriate, smaller models for simpler tasks, and evaluations that verify quality remains acceptable after each optimization. Describe how you would create reusable AI engineering components for other developers. I would identify common patterns such as model invocation, tool calling, retrieval, evaluation, tracing, and policy enforcement, then package them as documented libraries or templates. Adoption would be supported through clear interfaces, examples, automated tests, reference implementations, and feedback from early internal users. Next step ## Apply now. Follow the employer’s application method and review Jobicy’s safety guidance before sharing personal information. 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