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Added 14 mins ago
Staff Backend Engineer - Digital Credentials
Okta
Toronto, ON
$160,000 to $220,000 CAD / year
Full-time
…digital credentials. In a world with AI-driven fraud, one-time verification is no longer enough; the industry needs a reusable, tamper-proof way to prove identity at…
Added 1 hour ago
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Added 4 hours ago
Intermediate Software Engineer
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Toronto, ON
$90,000 to $110,000 CAD / year
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The Intermediate Software Engineer independently owns and delivers well-defined, small-to-medium complexity user stories end to end. You work AI-first by default: using Claude Code and…
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AltaML

Intermediate Software Engineer

Toronto, ON, Canada

Pay: $90,000 to $110,000 CAD / year
Job type: Full-time
Apply by: Oct 29, 2026
Experience: 2–4 years of professional software engineering experience.
Posting language: English
Posted: Sep 4, 2026

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Original job description

Engineering @ AltaML - How We Work:

We are an AI-first company. Claude Code and AltaML's shared configuration and skills library are the default way engineers design, build, test, and review software, not an optional accelerant a few people use.
We expect dramatically higher productivity from working this way. A step change, not a marginal gain. That's the baseline we hire and promote against, not an aspirational ceiling.
We believe AI has compressed what used to take weeks into days, and what used to take days into hours. Estimates, sprint commitments, and delivery timelines should reflect that reality, not pre-AI habits.
Show us, don't tell us. As part of applying, share an example of your AI-assisted coding: a PR, a repo, a recorded session, or whatever best demonstrates how you actually work with AI day to day.
We overpay for the right people. We'd rather pay a premium for an engineer who embodies this and multiplies the team than save money on someone who doesn't

The Intermediate Software Engineer independently owns and delivers well-defined, small-to-medium complexity user stories end to end. You work AI-first by default: using Claude Code and AltaML's shared skills library as your everyday workflow, not a novelty. And, you're building the judgment to take on increasingly novel problems without close supervision.

What You'll Do:

Feature Implementation & Bug Fixes (:65%)

Serve as the main contributor for small-to-medium complexity stories, including work that introduces patterns new to AltaML/AltaForge.
Use Claude Code and AltaML's shared CLAUDE.md/skills library as your default workflow for design, implementation, and review

Testing & Documentation (:15%)

Write comprehensive automated tests and clear documentation for novel code, ensuring long-term stability.

Code Review Participation (:10%)

Give constructive feedback that measurably improves the quality of peers' contributions.

Learning & Collaboration (:10%)

Build strong fluency in AltaML/AltaForge libraries and platforms and make sound technical choices independently.

What You Bring:

2–4 years of professional software engineering experience.
Daily, hands-on comfort with an AI coding assistant (Claude Code or equivalent) as a core part of how you work - or you pick one up fast.
Strong fundamentals in testing, Git, and at least one of Python, TypeScript, or C#.
Experience with a cloud platform (Azure, AWS, or GCP) is a plus.
Familiarity with LLM-based application development (LangChain, vector databases, LLM APIs) is a plus.

Nice to Have's:

Experience contributing to a shared component or config library.
Exposure to agentic workflows or GenAI product development.

What Success Looks Like

Independent Feature Velocity: Consistently owns and delivers small-to-medium complexity stories end to end with a fast, predictable cycle time - keeping delivery cost per story down.
AI-Accelerated Delivery: Visible, everyday use of AI-first workflows that meaningfully compresses cycle time - the weeks-to-days, days-to-hours shift we expect at every level.
Reusable Contribution: Regularly contributes novel code patterns or components that become candidates for shared libraries or AltaForge - supporting the AltaForge Clients and Same-Agent-Across-Clients north stars.
Technical Autonomy: Resolves the large majority of technical blockers independently, without routinely escalating to senior engineers.
Peer Quality Enhancement: Code review feedback that noticeably improves the quality of peers' work.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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More about this job

Responsibilities

Independently design, implement, test, and document small-to-medium software features and bug fixes, using Claude Code and AltaML’s shared skills library as the default workflow. Participate in code reviews, make sound technical decisions, and contribute reusable patterns while resolving most technical blockers independently.

Requirements

Requires 2–4 years of professional software engineering experience, hands-on use of an AI coding assistant or the ability to adopt one quickly, and strong testing and Git fundamentals. Candidates should be proficient in at least one of Python, TypeScript, or C#; cloud platform experience and familiarity with LLM application development are advantages.

Skills

Claude Code
AI-Assisted Coding
Python
TypeScript
C#
Automated Testing
Git
Code Review
Technical Documentation
Cloud Platforms
LLM Application Development
LangChain
Vector Databases
LLM APIs
Agentic Workflows
GenAI Product Development

Visa sponsorship

Not detected in the job text

Keywords

Claude Code
AltaML
AltaForge
AI-First Engineering
AI-Assisted Coding
Shared Skills Library
CLAUDE.md
Python
TypeScript
C#
Automated Testing
Git
Code Review
Technical Documentation
Azure
AWS
GCP
LLM Application Development
LangChain
Vector Databases
LLM APIs
Agentic Workflows
GenAI Product Development
Reusable Components
Feature Implementation
Bug Fixes

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