Software Developer, AI Platform Foundations
Backend Engineer · Mid · Full Time · Remote
Opens Wealthsimple Technologies's application page
Role
What you'll do.
Join Wealthsimple's AI Platform Foundations team to build shared AI tooling that empowers hundreds of engineers across a fintech organization serving 4M+ Canadians. As a Software Developer, you'll design LLM-integrated platform infrastructure, implement developer productivity features, and establish AI governance guardrails across a polyglot stack (Ruby, Python, TypeScript, Java/Kotlin). This role offers the opportunity to shape how AI-assisted engineering evolves at scale within a fast-growing financial technology company.
Responsibilities
- Design and Build Shared AI Tooling Platform: Architect well-scoped platform components that bring AI-assisted development capabilities to hundreds of engineers across Wealthsimple. Consolidate custom and one-off LLM tools into a unified, governed platform that teams can adopt with confidence and minimal friction, standardizing on reliable patterns and reducing technical debt from siloed AI integrations.
- Accelerate Developer Productivity through AI Features: Build and ship AI-powered developer tools that reduce friction in the development lifecycle, including intelligent code review analysis, automated pull request helpers, smart deployment verification, and other automation that frees developers to focus on high-value work while maintaining code quality.
- Implement Governance and Guardrail Systems: Design and build policy controls, verification layers, and compliance enforcement mechanisms that keep AI interactions across the organization safe, compliant, and aligned with Wealthsimple standards. Identify potential risks early, document security implications, and ensure components you build maintain reliability so issues are caught before reaching production.
- Engineer Across Polyglot Technology Stack: Develop platform features and automation tools that work seamlessly across Ruby on Rails, Python, TypeScript, and Java/Kotlin environments. Understand how your implementations impact engineers in each ecosystem and ensure parity of experience while meeting teams where they are with their preferred tools.
- Drive Data-Informed Decision Making: Implement instrumentation and metrics collection to measure the adoption, impact, and effectiveness of platform features. Use observability data to validate assumptions about developer productivity, identify optimization opportunities, and help inform prioritization of future platform capabilities.
- Establish AI Engineering Best Practices: Propose well-reasoned technical solutions backed by research and data, experiment with emerging LLM tools and approaches, and contribute to establishing patterns and practices around LLM integrations, cost awareness, token management, and platform extensibility across the organization.
- Collaborate and Build Team Capability: Work closely with Platform Engineering partners and other teams across the organization to understand their needs and constraints. Share knowledge through documentation and thoughtful code reviews, give meaningful feedback to peers, help onboard new team members, and grow your craft alongside more experienced engineers.
Qualifications
What we look for.
Technical
LLM and AI System Integration
Practical experience or strong ongoing learning in integrating large language models into production systems, understanding model capabilities, API patterns, cost implications, and error handling strategies specific to AI-powered features.
Backend System Design
Demonstrated ability to design and implement reliable backend components, APIs, and infrastructure services that serve multiple teams and maintain high availability and performance standards.
Platform and Developer Tooling Architecture
Understanding of how to build developer-focused infrastructure, internal platforms, and tools with emphasis on adoption, usability, and minimal friction for downstream engineering teams.
Policy and Governance Implementation
Experience building systems that enforce organizational policies, compliance requirements, or security standards through automated checks and verification layers rather than manual processes.
Observability and Metrics
Ability to implement instrumentation, metrics collection, and analysis to measure system performance, developer adoption, and business impact of platform features.
Education
Computer Science or Related Field
Bachelor's degree in Computer Science, Software Engineering, or related technical discipline, or equivalent professional experience demonstrating strong foundations in computer science fundamentals.
Experience
Professional Software Development
Minimum 3+ years of professional software development experience working as part of engineering teams, demonstrating ability to ship production features, collaborate across codebases, and respond to feedback effectively.
Platform or Developer Experience Work
Some hands-on experience or demonstrable interest in platform engineering, developer tools, or developer experience initiatives that shows understanding of how infrastructure impacts engineering velocity.
LLM-Powered Development
Practical experience building LLM-powered developer tools, integrating AI APIs into applications, or experimenting with AI agents and automation, demonstrating understanding of both opportunities and practical constraints of production AI systems.
Skills
Required
Software Development
3+ years of professional software development experience working within teams, with demonstrated ability to design and implement well-scoped components and ship production features across multiple development cycles.
Programming Languages
Working proficiency in at least one of Ruby, Python, TypeScript, or Java/Kotlin with demonstrated comfort learning and working across multiple languages as project requirements evolve.
LLM and AI Integration
Hands-on experience building with large language models and AI tooling, including experience integrating AI APIs, implementing LLM-powered features, or experimenting with AI-assisted automation in practical applications.
Platform and Developer Tooling
Experience or strong exposure to platform engineering, developer experience initiatives, or building internal developer tools with understanding of how to design for engineering end-users.
Policy and Governance Systems
Interest in building systems that enforce organizational standards and compliance requirements without creating friction for developers, with experience implementing governance, policy controls, or guardrail mechanisms preferred.
Collaboration and Communication
Strong ability to work effectively with cross-functional teams, communicate progress and blockers transparently, discuss technical trade-offs clearly, and coordinate across platform engineering partners.
Data-Driven Decision Making
Ability to use metrics and observability to measure the impact of implementations, inform prioritization decisions, and validate assumptions about developer productivity and system performance.
Preferred
Fintech or Financial Services Domain Knowledge
Nice to haveExperience working in financial technology, regulated environments, or building infrastructure for compliance-sensitive organizations strengthens understanding of governance and risk requirements.
Developer Experience Mindset
Nice to haveTrack record of thinking about internal tools and platforms as products, understanding developer pain points deeply, and building solutions that achieve strong adoption and satisfaction metrics.
Mentorship and Knowledge Sharing
Nice to haveExperience contributing to team growth through documentation, code reviews, technical mentoring, or helping onboard new engineers demonstrates collaborative maturity.
Production AI/LLM Systems
Nice to havePrevious experience shipping production systems that integrate large language models, managing LLM-specific concerns like cost optimization, latency, and model versioning.
CI/CD and Deployment Tooling
Nice to haveFamiliarity with continuous integration, continuous deployment, and the automation and verification layers that enable safe code review and production deployment processes.
Tech stack
Languages
Frameworks
Databases
Tools
Other
Compensation
Pay and benefits.
Base·CAD 123,200 – 154,000
Equity·Stock options
Benefits
Health and Wellness Benefits
Top-tier health insurance coverage, dental and vision care, life insurance, and comprehensive health benefits that support your wellbeing.
Flexible Time Off
20 vacation days annually plus 4 dedicated wellness days and unlimited sick and mental health days, providing flexibility to manage your work-life balance and personal wellbeing.
Global Mobility Program
Work remotely from outside Canada for up to 90 days per year, enabling you to travel, explore different environments, and maintain flexibility in how you structure your work year.
Long-Term Savings and Matching
Group savings program through Wealthsimple for Business with employer matching contributions, helping you build long-term financial security alongside your compensation.
Employee Resource Groups
Access to vibrant employee resource groups including Rainbow (2SLGBTQ+), Women of Wealthsimple, and Black at Wealthsimple that foster community and belonging within the organization.
Hybrid Work Environment
Hybrid work arrangement with teams distributed across North America, offering flexibility to work remotely or from office locations as suits your working style and collaboration needs.
Collaborative Culture
Work alongside over 1,500 talented, driven, and curious colleagues across North America who are deeply committed to high-quality work and building products that matter in the fintech space.
Process
Interview steps.
- 01
Application and Resume Review
Your resume and application will be reviewed by the hiring team. Wealthsimple may use AI tools to support initial application screening and resume analysis, but all substantive hiring decisions are made by people. Highlight your experience with LLM integration, platform engineering, and developer tooling.
- 02
Initial Technical Screening Call
A conversation with a Platform Engineering team member to discuss your background, your experience with AI and LLM systems, your approach to platform design, and your interest in the role. Come prepared to discuss specific examples of platforms or tools you've built or contributed to.
- 03
Technical Interview
Deeper technical discussion focused on system design, LLM integration patterns, platform architecture decisions, and how you approach building developer tools. You may be asked to discuss how you'd design specific platform components or handle architectural trade-offs.
- 04
Collaboration and Product Thinking Assessment
Conversation centered on your product mindset, how you think about developer experience, your approach to gathering requirements from internal teams, and how you've collaborated with cross-functional partners. This evaluates your thinking around platform adoption and developer satisfaction.
- 05
Team and Culture Fit Discussion
Discussion with members of the AI Platform Foundations team about team dynamics, your approach to mentorship and learning, how you contribute to team culture, and your interest in growing with the team. This is an opportunity to learn about day-to-day collaboration and team values.
- 06
Offer and Negotiation
If selected, you'll receive an offer including compensation, equity details, benefits, and other details. Wealthsimple welcomes discussion about compensation and benefits to ensure alignment with your expectations and circumstances.
Full posting
Original listing.
Build something people love
Wealthsimple is Canada’s leading financial innovator. The company offers a full suite of simple, sophisticated financial products across managed investing, do-it-yourself trading, cryptocurrency, tax filing, spending and saving. Wealthsimple currently serves more than 4 million Canadians and holds over $125 billion in assets under administration. The company was founded in 2014 by a team of financial experts and technology entrepreneurs, and is headquartered in Toronto, Canada.
We're proud of what we've built — and we're just getting started. Read our Culture Manual and learn more about how we work.
About the AI Platform Foundations Team
AI Platform Foundations is a team within Platform Engineering on a mission to make AI a reliable, governed, and productivity-multiplying force across Wealthsimple's engineering organization. We build and maintain the shared AI tooling that hundreds of developers depend on to ship faster and with more confidence. We also build the guardrails and policy controls that keep teams on the golden path, so innovation happens without introducing risk.
You'll help build what AI-assisted engineering looks like at Wealthsimple. You'll work in a polyglot environment of Ruby on Rails, Python, TypeScript, and Java/Kotlin, partnering with teams across Platform Engineering to build tooling that is adopted broadly, trusted deeply, and measured rigorously. Your work will directly influence how Wealthsimple's engineers write code, review changes, and ship to production.
In this role you'll have the opportunity to:
Contribute to building the shared AI tooling platform. Working alongside the team, you'll design and implement well-scoped components of the shared infrastructure that brings AI-assisted development to teams at Wealthsimple. You'll help consolidate one-off and custom LLM tools into a governed, reusable platform that engineering teams can adopt with confidence.
Accelerate developer productivity through AI-powered automation. Build features and tooling that reduce friction in the development lifecycle from AI-assisted code review checks and automated PR helpers to intelligent deployment checks so developers can focus on what matters most.
Implement guardrails that keep developers on the golden path. Build policy controls and verification layers that help keep AI interactions across the organization safe, compliant, and aligned with Wealthsimple's standards. You'll identify and raise potential risks early, and take ownership of the reliability of the components you build so issues are caught before they reach production.
Ship across a polyglot engineering stack. Work with tooling and automation across Ruby on Rails, Python, TypeScript, and Java/Kotlin to meet developers where they are. You'll understand how the features you build impact the engineers who use them, and use metrics on your own work to help inform what to build next.
Help shape how we approach AI-assisted engineering at Wealthsimple. Propose well-reasoned solutions backed by data and research, experiment with new tools and approaches, and contribute to the patterns and practices the team establishes around LLM integrations, cost awareness, and tooling.
Grow your craft and support your teammates. Share what you learn through documentation and code reviews, give meaningful feedback to peers, help onboard new team members, and continue growing with guidance from senior and staff engineers on the team.
What you'll bring:
3+ years of software development experience as part of a team, ideally including some exposure to platform engineering, developer experience, or developer tooling, and a growing interest in AI-powered or LLM-driven systems.
Some hands-on experience or strong interest in building with LLMs and AI tooling. Whether you've built LLM-powered developer tools, integrated AI APIs, or experimented with agents and automation, you're eager to understand the practical realities of working with models like Claude in production systems.
A developing product mindset for internal platforms. You think of developer tooling as a product, with engineers as your customers. You're curious about their pain points and motivated to build solutions that stick.
Working proficiency in at least one of Ruby, Python, TypeScript, or Java/Kotlin, and a willingness to work across others as needed. You're building growing proficiency in a team's technical stack and comfortable writing tooling and automation.
An interest in building systems that enforce standards without getting in developers' way. Direct experience with governance, policy, or guardrail systems is a plus.
Comfort making data-informed decisions. You use metrics to understand the impact of your work and to help prioritize what to do next.
Solid collaboration skills. You build good working relationships with your immediate partners and communicate clearly about progress, blockers, and trade-offs.
A collaborative spirit and a growing interest in mentorship. You're beginning to share your knowledge with peers, give constructive feedback, and are eager to keep learning from more experienced engineers.
Why Wealthsimple?
🌸 Top-tier health benefits and life insurance
📈 Long-term group savings with employer match, through Wealthsimple for Business
🌴 20 vacation days, 4 wellness days, and unlimited sick and mental health days per year
✈️ 90 days away: work outside Canada for up to 90 days per year
👥 Employee resource groups, including Rainbow (2SLGBTQ), Women of WS, and Black at WS
🌎 We are a hybrid team with over 1,500 employees across North America. The people are one of the best parts of working here: you'll collaborate with incredibly talented, curious, and driven teammates who are deeply committed to doing great work.
ICYMI
Technology & Innovation at Wealthsimple: We move quickly and build thoughtfully. That means we're always looking for better ways to work — whether that's new tools, AI, or rethinking how we approach a problem. We don't expect you to have all the answers, but we do expect curiosity and a willingness to evolve alongside the products we're building.
Inclusion Statement: We're building products for a diverse world, and we need a diverse team to do it well. We strongly encourage applications from everyone, regardless of race, religion, colour, national origin, gender, sexual orientation, age, marital status, or disability status.
Accessibility Statement: We're committed to an accessible hiring experience. If you need any accommodations throughout the interview process, please let us know — we'll work with you to make sure you have what you need. We also welcome any feedback on how we can better accommodate candidates with accessibility needs.
AI in Hiring: We may use artificial intelligence (AI) tools to support parts of our hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our team but don't replace human judgment – all final hiring decisions are made by people. If you have questions about how your data is used, reach out to us.
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