Staff Software Engineer, Delivery Engineering.

Accountabilities

• Define and evolve the end-to-end agentic software development lifecycle, covering change identification, planning, execution, pull requests, merging, and impact measurement.

• Evaluate AI coding agents, agent harnesses, repository patterns, MCP integrations, skills, and related tooling to establish effective standards and shared engineering practices.

• Build, maintain, and support internal platforms and developer tools that enable engineering teams to deliver software more efficiently, reliably, and securely.

• Collaborate directly with engineering teams to understand their workflows, identify bottlenecks, and develop solutions that fit their operational needs.

• Drive adoption of shared tools and workflows, taking ownership of both successful delivery and sustained usage across the organization.

• Instrument and analyze agent usage, engineering throughput, software quality, reliability, and token consumption to measure outcomes and guide improvements.

• Evaluate AI models, vendors, and open-source solutions, making informed build-versus-buy decisions based on engineering needs, cost, and reliability.

• Lead technical design discussions, document architectural decisions and trade-offs, influence cross-team engineering strategy, and mentor engineers adopting AI-driven development practices.

Requirements

• At least 8 years of professional software engineering experience, including responsibility for production systems and technical decisions that affect multiple teams.

• Demonstrated experience leading initiatives that meaningfully changed how an engineering organization develops software using AI agents, including measuring results, driving adoption, and learning from unsuccessful approaches.

• Strong hands-on experience with agentic development tools, coding agents, agent harnesses, Model Context Protocol (MCP), and skills or prompt design.

• Ability to evaluate AI-generated code and agent performance, with a practical understanding of model selection, token economics, cost optimization, and reliability considerations.

• Proven experience building and maintaining internal platforms or developer tooling that other engineering teams depend on, including responsibility for adoption and long-term effectiveness.

• Strong backend engineering expertise in Go, including ownership of production services, API design, data modeling, and service integration.

• Excellent technical judgment and problem-solving skills, with the ability to turn the needs of multiple teams into clear priorities, documented decisions, and actionable engineering direction.

• Strong communication, collaboration, and leadership skills, including the ability to influence stakeholders, lead technical discussions, and mentor engineers without relying solely on formal authority.

• A user-focused mindset and enthusiasm for experimenting with emerging AI technologies to solve practical engineering challenges.

Benefits

• Competitive salary: Canadian base salary range of CAD 195,000–265,000, depending on qualifications, experience, and other relevant factors.

• Remote work: Remote opportunity for eligible candidates based in Canada’s Eastern time zone.

• Comprehensive benefits: Benefits designed to support employee health and well-being, including coverage of up to 100% for employees, subject to the applicable benefit plan.

• Paid time off: Generous time off to rest, recharge, and maintain work-life balance.

• Mental health support: Holistic mental health resources and support.

• Professional development: Opportunities to learn new skills through project-based learning and presentations from colleagues.

• Flexible work environment: A flexible approach to where employees work, with opportunities to connect and build community.

• Accessibility and accommodations: Reasonable accommodations are available for candidates with disabilities during the application and interview process and throughout employment.