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Added 2 months ago
Senior, AI & Data Science
Welcome to the Jungle
Montreal, QC
Comfort with AI-assisted development tools such as Claude Code, Gemini CLI, or Cursor.
Added 2 months ago
AA
Lead Product Manager, Inspections
ACV Auctions
Toronto, ON
- Full-time
…for you! Competitive compensation packages and learning and development opportunities, ACV has what you need to advance to the next level in your career. We will continue to raise the bar…
Added 2 months ago
UT
Senior Machine Learning Engineer
Unity Technologies
Montreal, QC · CAN-Montreal
- Full-time
Added 2 months ago
Senior Principal Industry Analyst Relations
PagerDuty
Toronto, ON
…competencies to give leaders a shared language for guiding their development, career, promotion, and succession planning discussions. Our Manager Expectations serve as a practical guide for…
Added 2 months ago
TR
Lead Cloud Platform Engineer, Azure
Thomson Reuters
Toronto, ON · Canada, Toronto, Ontario
- Full-time
Added 2 months ago
C
Staff Backend Software Engineer
Cognichip
Toronto, ON
- $184,000 to $225,000 CAD / year
- Full-time
We are seeking a Staff Backend Software Engineer to spearhead the development of our platform applications and services. You will architect critical backend solutions, including usage…
Added 2 months ago
B
Software Engineer - Continuous Delivery
Baseten
Montreal, QC
- $165,000 to $330,000 USD / year
- Full-time
…applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing…
Added 2 months ago
B
Software Engineer - AI Developer Productivity
Baseten
Montreal, QC
- $165,000 to $330,000 USD / year
- Full-time
…applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing…
Added 2 months ago
H
Director, Data & AI (Hybrid)
Homebase
Toronto, ON
- $230,000 to $273,000 CAD / year
- Full-time
…with AI tools and workflows. Drive adoption of AI-assisted development practices (agentic coding, AI-augmented analytics). Measure and share…
Added 2 months ago
PA
AI Modeling Engineer
Palona AI
Toronto, ON
- Full-time
…speech and language quality, evaluation methodology, dataset development, and model behavior in…
Added 2 months ago
VN
Solutions Architect, AI Systems
Viral Nation
Toronto, ON
- Full-time
…AI-driven products - not just models and dashboards, but working software that…
Added 2 months ago
J
Manager, Credit Risk
Jobber
Remote, Canada
- Full-time
- Remote
Added 2 months ago
V
Machine Learning Engineer Lead
Vancity
Vancouver, BC · Toronto, ON
- Full-time
…You will work across the full ML lifecycle, including model development, feature engineering, MLOps, deployment automation, monitoring, and continuous improvement of machine learning…
Added 2 months ago
PX
Data Scientist (AI/ML)
Project X
Toronto, ON
- Full-time
Participate in the development of project plans to establish appropriate workload expectations and schedules.
Added 2 months ago
A
Intern, AI Developer/ Stagiaire en développement IA
Autodesk
Montreal, QC
- Full-time
Currently enrolled in a Bachelors degree in Computer science, software engineering with a minor in AI or MS degree in Computer Science, Mathematics or similar field; Ph.D. degree is a big…
Added 2 months ago
C
Senior Backend Developer - ML Platform
Coveo
Montreal, QC · Greater Montreal Metropolitan Area
- Full-time
Contribute to the development lifecycle, including coding, testing, and deployment
Added 2 months ago
M
Senior Frontend Engineer (Tech Lead)
Meltwater
Toronto, ON
- Full-time
You will lead the development and evolution of our frontend platform, driving both team execution and the broader technical direction of the UI across the product. This role combines…
Added 1 month ago
VA
Member of Technical Staff - ML Operations
Veeda AI
Remote, Canada
- Full-time
- Remote
End-to-End Ownership: Lead projects through the complete software lifecycle, including technical specs, implementation, CI/CD, on-call support, and production observability.
Added 2 months ago
XR
AI Platform & Machine Learning Engineer
XYZ Reality
Remote, Canada
- Full-time
- Remote
Working closely with our Computer Vision, Navigation, Embedded Software and Cloud Engineering teams, you’ll help ensure our AI models can be trained, evaluated, deployed and continually…
Added 2 months ago
1
Business Development Representative
1Password
Remote, Canada
- Full-time
- Remote
As a Business Development Representative, you play a pivotal role in driving our sales pipeline. With a strong focus on outbound prospecting, you proactively identify and engage…
Added 2 months ago
S
Senior Software Developer
SOTI
Mississauga, ON
- Full-time
You’re a strong technical thinker with a solid foundation in software development and a deep understanding of how complex systems work under the hood. As a Senior Software Developer on our…
Added 2 months ago
B
Software Engineer - Observability
Baseten
Montreal, QC
- $165,000 to $330,000 USD / year
- Full-time
…applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing…
Added 2 months ago
VG
[VO2 Canada] -Ingénieur.e IA / LLM – Missions Ponctuelles
VO2 GROUP
Montreal, QC
- Full-time
Added 3 months ago
X
Data Scientist
Xsolla
Canada
- Full-time
…career roadmap for each employee. By investing in professional development through training and educational opportunities, we ensure that our team thrives both personally and…
Added 2 months ago
SI
Director of Product, Content Intelligence & Growth
Scribd, Inc.
Vancouver, BC · Ottawa, ON · Toronto, ON
- Full-time
Partner with business development on evolving corpus intelligence needs.

Baseten

Software Engineer - AI Developer Productivity

Montreal, QC, Canada

$165,000 to $330,000 USD / year · Full-time

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Job details

Pay: $165,000 to $330,000 USD / year
Job type: Full-time
Experience: Have 4+ years of relevant industry experience building and enabling AI native SDLC
Posting language: English
Posted: Aug 11, 2026

Original job description

About Baseten

Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products.

THE ROLE

Baseten's engineers want to work in an AI-first way. What's missing isn't enthusiasm - it's the platform underneath it. Today everyone assembles their own agent config, context files, and MCP servers, so the good patterns stay trapped in individual setups instead of becoming defaults everyone inherits.

You'll build that platform: the agent configurations tuned to our monorepo, the context and tooling layer that makes agents competent in our codebase, the evals that tell us which approaches actually work, and the rollout mechanics that get a new engineer productive with agents in week one.

You are not here to mandate how engineers use AI - you're here to make the good path the easy path. Success looks like teams adopting what you build because it beats what they'd cobble together themselves, not because a policy requires it. Platform engineer, not AI evangelist. Ship infrastructure, measure it, kill what doesn't work, let adoption be the referee.

The playbook for AI-first SDLC doesn't exist at any company yet. You'll write ours.

What You'll Build

Agent substrate - Repo-level context infrastructure that makes agents competent in our codebase (CLAUDE.md/AGENTS.md conventions, architecture and domain context, and the tooling to keep it accurate as code moves). Internal MCP servers giving agents scoped access to CI, observability, incident tooling, deployment state, and docs. Shared skills, subagents, and hooks that encode Baseten workflows. Sandboxed environments where agents can build and test safely.

The golden path - Project templates and onboarding that ship with AI tooling configured and working. Self-serve infrastructure so teams build their own agents without you as the bottleneck. Gateway, auth, cost controls, and audit logging for internal model access.

The feedback loop - Eval harnesses that answer "is this config better than that one" against real Baseten tasks, not vibes. Instrumentation of AI tool usage and its downstream effects on cycle time, review latency, and change failure rate. Honest reporting, including on what you built that didn't pan out.

Agents in the SDLC - Automation where agents earn their keep: PR review triage, test gap-filling, incident context assembly, migrations and refactors, codebase Q&A. Integrating agents into CI/CD with guardrails that make it trustworthy.

Responsibilities

Own the internal AI developer platform end to end - architecture, build, rollout, operation, measurement.
Evaluate and integrate third-party AI coding tools (Claude Code, Cursor, Codex, and whatever ships next quarter), and build the context layer that makes them work against our monorepo.
Build frameworks that let other engineers create their own agents without deep LLM expertise.
Establish the evaluation practice for AI-assisted development at Baseten, and use it to drive investment decisions.
Drive adoption through developer experience - good defaults, clear docs, low friction - not mandate.
Embed with teams to find where AI genuinely unblocks them, then generalize those wins into platform capabilities.
Own the safety layer: permissions, secrets handling, audit trails, cost management.

Requirements

Have 4+ years of relevant industry experience building and enabling AI native SDLC
Strong proficiency in Python and/or Go, building tools other engineers depend on daily.
Hands-on experience with LLMs and agent frameworks - tool calling, MCP, context management, orchestration, failure handling. You've shipped something agentic that real people used, not just prototyped.
Deep personal fluency with AI coding tools and well-formed opinions about where they break down.
Platform mindset: you build for adoption and self-service, treat internal engineers as customers, and would rather ship a good default than write a style guide.
Developer tooling, CI/CD, and Kubernetes/Docker fundamentals.
Comfort with ambiguity - this space invalidates its own best practices every few months.
Excellent written communication. Much of your leverage is docs, templates, and examples that scale beyond conversations you're in.

Benefits

Competitive compensation, including meaningful equity.
100% coverage of medical, dental, and vision insurance for employee and dependents
Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
Paid parental leave
Fertility and family-building stipend through Carrot
Company-facilitated 401(k)
Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.

Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.

At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.

We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Compensation Range: $165K - $330K

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More about this job

Responsibilities

Build and own the internal AI developer platform to optimize the software development lifecycle through agentic tooling and infrastructure. Create repo-level context layers, MCP servers, and evaluation harnesses to improve engineer productivity and AI adoption.

Requirements

Requires 4+ years of industry experience building AI-native SDLC tools with strong proficiency in Python or Go. Must have hands-on experience shipping agentic systems and a deep understanding of LLM orchestration and platform engineering.

Skills

Python
Go
LLMs
Agent Frameworks
MCP
Context Management
CI/CD
Kubernetes
Docker
Platform Engineering
Developer Tooling
Orchestration
API Design
Technical Documentation
Evaluation Frameworks
Infrastructure as Code

Benefits

Competitive compensation
Meaningful equity
Medical insurance
Dental insurance
Vision insurance
Flexible PTO
Winter Break
Paid parental leave
Fertility and family-building stipend
401(k)

Visa sponsorship

Not detected in the job text

Keywords

AI Developer Productivity
LLM
Agentic Workflows
MCP Servers
Monorepo
SDLC
Python
Go
Kubernetes
Docker
CI/CD
Claude Code
Cursor
Codex
Evaluation Harnesses
Platform Engineering
Developer Experience
Infrastructure
Tool Calling
Context Management
Audit Logging
Cost Controls
PR Review Triage
Observability
Incident Tooling
Software Engineering
Machine Learning
AI-First
Automation
Developer Tooling

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