Staff Engineer

Canada·TorontoFull-timelead

OtherStaff Engineer

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Technical Tools

OtherStaff Engineer

Managing pricing and rebates shouldn’t be a hassle. Enable’s intelligent platform is built for the speed of today’s market, eliminating disconnects between pricing strategy and rebate execution. We help companies to increase profitability and simplify the complex with accurate, AI-powered insights, real-time performance monitoring, agreement optimization, and simplified rebate management.

After securing $291M in Series A-D funding and acquiring Flintfox in 2025, Enable is positioned for continued, significant growth. Since the launch of our flagship product in 2016, we have been rapidly scaling our client base, product offerings, and built a team of top-tier professionals committed to reshaping the industry.

Want a glimpse into life at Enable? Visit our Life at Enable page to learn how you can be part of our journey.

As Staff Engineer, you will own the technical strategy across multiple teams and product areas. You’ll define reference architectures, establish engineering-wide standards, and drive the adoption of AI-native development practices that make every team at Enable more effective. Your influence is felt in every codebase, every architecture decision, and every engineering hire.

You’ll work directly with engineering leadership and product stakeholders. You’ll write code. You’ll review code. You’ll debug production incidents at 2am when the situation demands it. And you’ll do all of this while shaping how Enable’s engineering organisation evolves for an AI-augmented future.

Technical strategy and architecture — Own the technical direction across multiple product areas. Define reference architectures for AI-native systems, establish patterns for agent orchestration, RAG pipelines, and human-AI collaboration workflows that teams can adopt consistently. Make strategic build-versus-buy decisions that affect the entire platform.

Hands-on engineering leadership — Write and ship production code regularly. Conduct technically rigorous architecture and code reviews. Debug the hardest cross-system problems. You lead by doing, not by directing from a distance. Your credibility comes from the quality of your technical contributions, not your title.

AI-native engineering practices — Define Enable’s approach to AI-assisted development — evaluating new tools, establishing governance for AI-generated code, building shared prompt libraries and evaluation frameworks, and shaping engineering-wide standards that maximise productivity while maintaining quality. Your recommendations are grounded in daily, hands-on use of these tools.

Cross-team technical alignment — Drive architectural consistency across team boundaries. Identify cross-cutting concerns, resolve technical disagreements, and ensure that multiple teams building towards shared goals are doing so with compatible designs and shared infrastructure. Build the connective tissue between teams that prevents fragmentation.

Engineering quality and reliability — Set the bar for engineering excellence across the organisation. Establish quality standards for AI-augmented systems, drive observability and monitoring practices, and ensure Enable’s platform is secure, performant, and reliable. Own the response to the most critical production incidents.

Technical mentorship and uplift — Raise the technical capability of every team you touch. Mentor senior engineers towards staff-level thinking. Build communities of practice around AI-native engineering. Create the learning pathways, documentation, and shared knowledge that make the entire engineering organisation stronger.

Responsible AI governance — Establish standards for AI safety, security, and quality across Enable’s products. Define evaluation frameworks for AI system outputs. Ensure AI integrations meet security standards, including prompt injection prevention and model output validation. Collaborate with product, security, and legal teams to ensure compliance.

DevOps and tooling innovation — Drive Enable’s AI-augmented development platform forward. Evaluate and adopt tools that leverage AI for deployment safety, intelligent monitoring, automated code review, and predictive scaling. Shape the toolchain that every engineer at Enable uses daily.

10+ years of software engineering experience, with clear progression in scope, complexity, and technical leadership. You have operated at staff level or equivalent — owning technical strategy across multiple teams, not just writing code in one

Deep proficiency in at least two modern programming languages and strong working knowledge across multiple paradigms. You can review and contribute to code across different parts of the stack with credibility

Proven track record designing and shipping distributed systems at scale — microservices, event-driven architectures, cloud-native platforms. You’ve made architectural decisions that held up under real production load

Hands-on experience building AI-powered product features — LLM integrations, RAG architectures, agent orchestration, embedding pipelines, or similar. You understand AI system design from implementation, not just theory

Strong experience with cloud platforms (Azure preferred), container orchestration, CI/CD pipelines, and modern DevOps practices. You’ve designed infrastructure, not just deployed to it

Daily, proficient use of AI coding assistants (Copilot, Claude, or equivalent). You have a developed personal workflow for AI-assisted development and strong opinions on what works and what doesn’t

Experience defining and driving engineering-wide technical standards, architectural patterns, and development practices across multiple teams

Data systems expertise — relational and non-relational databases, and ideally vector databases, embedding pipelines, and data architectures for AI workloads

SaaS product development experience, ideally B2B. You understand the constraints and rhythms of building products that real businesses depend on

You are technically relentless. You don’t stop at the architectural diagram — you follow through into implementation, review, debugging, and production operations. You are as comfortable in a codebase as you are in a design meeting

You have strong opinions, loosely held. You drive technical alignment through influence and evidence, not authority. When you’re wrong, you change course quickly and openly

You are a force multiplier. You measure your impact not just by what you build, but by how much better you make everyone around you. Teams ship better software after you’ve been involved

You are pragmatic about AI. You’re excited about what AI tools can do, but you don’t chase hype. You evaluate tools critically, adopt what genuinely works, and are honest about limitations

You communicate with clarity and directness. You can explain complex technical decisions to non-technical stakeholders and defend them under scrutiny. You write as well as you code

You take ownership beyond your remit. You see a problem, you fix it — regardless of whether it’s in your team, your codebase, or your job description

You care about craft. Code quality, system reliability, developer experience, documentation — the things that separate engineering organisations that thrive from those that merely function

A degree in computer science, software engineering, or a related technical field — or equivalent experience that demonstrates the same depth. What matters is what you can do, not what’s on the certificate