Senior Software Engineer (Artificial Intelligence)

• We’re looking for a Senior Software Engineer to join our growing AI organization in Vancouver
• Asana is pioneering a new category of technology as the human-agent operating system, doubling down on our AI Suite to move our customers toward expansive, end-to-end intelligent orchestration
• We are expanding several of our key AI engineering teams: depending on where you land, you might lead architecture across our core agentic runtime, develop high-throughput evaluation and safety infrastructure, or build the sophisticated customer-facing builders and canvas surfaces that allow enterprises to coordinate humans and AI agents seamlessly
• Because this is an organization-wide search across our AI teams, you will participate in a single, streamlined technical interview process, and we will work with you to match you to the ideal team at the end of your interview experience
• This role is based in our Vancouver office with an office-centric hybrid schedule
• The standard in-office days are Monday, Tuesday, and Thursday
• Most Asanas have the option to work from home on Wednesdays
• Working from home on Fridays depends on the type of work you do and the teams with which you partner
• If you’re interviewing for this role, your recruiter will share more about the in-office requirements
• Drive the technical design, architecture, and end-to-end delivery of medium-to-large projects across our AI roadmap, guiding and collaborating with multiple engineers
• Design robust, extensible, and performant systems that support agentic execution, prompt-driven automation, model orchestration, and strict enterprise-grade data boundaries
• Solve complex technical problems by weighing technical debt, developer velocity, execution risk, and direct business goals
• Anticipate customer and architectural risks early, breaking down complex, ambiguous product visions into clear engineering milestones and actionable tasks
• Champion technical excellence, write high-leverage design docs, run meaningful retrospectives, establish testing norms, and mentor engineers across levels to raise the engineering bar
• Partner closely with Product Managers, Engineering Managers, Product Designers, and Data Scientists to define requirements, clarify trade-offs, and align technical direction with Asana’s broader product strategy

Benefits

• Benefits - From comprehensive health benefits including mental health programs and coaching to our in-house culinary program and supportive parental leave policies, our benefits are intentionally designed to ensure that you are energized, focused, and thriving
• Development: We know that growth isn’t always linear, so we’ll support you in achieving your personal and professional goals. You’ll have the opportunity to take on big responsibilities that impact our success as a company and challenge you in new and fulfilling ways.
• Career growth: Your growth at Asana centers on ownership, access, and choice. All employees can tap into resources that support their growth and their team’s growth in the way that works best for their unique needs.

• Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making
• Track record of acting as a Tech Lead or Area of Responsibility (AoR) owner—successfully driving multi-contributor projects from ambiguity to delivery while navigating cross-team dependencies
• Deep empathy for the end-user experience, understanding how backend architecture and model behaviours directly affect user trust, interface latency, and workflow reliability
• Passion for mentoring and coaching fellow engineers, providing actionable code and design feedback, and establishing long-term engineering best practices
• Proven ability to author comprehensive technical design docs, evaluate trade-offs (e.g., latency, cost, determinism, maintainability), and make durable architectural decisions
• Demonstrated track record of technical leadership across multiple services or codebases, with practical experience or deep interest in LLMs, agentic patterns, evaluation pipelines, retrieval-augmented generation (RAG), or real-time streaming infrastructure
• 6+ years of professional software engineering experience designing, building, and maintaining production distributed systems, microservices, or complex full-stack architectures