Staff Engineer

Enable • Toronto, ON

16d

About The Position

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.

Requirements

• 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

Responsibilities

• 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.

Benefits

• Paid Time Off: Take the time you need to relax and recharge
• Wellness Benefit: Quarterly incentive dedicated to improving your health and well-being
• Comprehensive Insurance: Health and life coverage for you and your family
• Retirement Plan: Build your future with our retirement savings plan
• Lucrative Bonus Plan: Enjoy a rewarding bonus structure subject to company or individual performance
• Equity Program: Benefit from our equity program with additional options tied to tenure and performance
• Career Growth: Explore new opportunities with our internal mobility program
• Training: Access a range of workshops and courses designed to boost your professional growth and take your career to new heights
• Pets: Bring your pets to our welcoming, pet-friendly offices

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level