Full-time | Hybrid | Toronto | $180K-$260KAbout the RoleWe're looking for a AI Deployment Engineer with 3-6 years of experience to work closely with portfolio businesses, understand their operational challenges, and build production-grade AI and agentic solutions that create measurable impact. This is a highly hands-on engineering role. You'll work directly with business operators and technical teams, taking projects from identifying the right opportunity through development, deployment, optimization, and handoff. You'll have the opportunity to build systems that are actively used in real-world operations rather than working solely on prototypes or internal tooling.
What You'll Do- Work directly with portfolio companies to understand their workflows, pain points, and business priorities.
- Identify high-impact opportunities where AI and agentic workflows can improve efficiency or outcomes.
- Build and deploy end-to-end solutions, including backend integrations, agent workflows, prompts, evaluations, and user-facing interfaces.
- Monitor production systems and continuously improve their reliability, performance, and level of autonomy.
- Partner closely with general managers and other non-technical stakeholders to translate business needs into practical technical solutions.
- Take ownership of deployments from initial discovery through production rollout and stabilization.
- Document successful approaches, technical patterns, and lessons learned so they can be reused across other businesses.
- Travel regularly to portfolio company locations and work closely with teams on-site.
What We're Looking For- 3-6 years of experience in full-stack engineering, customer-facing software engineering, solutions engineering, or forward-deployed engineering.
- Strong full-stack development skills, including TypeScript or Python, React, and SQL.
- Experience building and deploying production LLM or agentic applications, rather than experimental demos alone.
- Familiarity with evaluations, monitoring, autonomy controls, and measuring outcomes for AI-powered systems.
- Experience working directly with customers, operators, or business stakeholders.
- Ability to independently take a project from understanding the problem through implementation and production deployment.
- Strong business judgment and the ability to understand operational workflows and translate them into technical solutions.
- Comfortable communicating with both highly technical and non-technical stakeholders.
- Location & Work ModelToronto
- Hybrid role with a minimum of 3 days per week in-office; 4 days preferred.
- Approximately 2-3 days per week of domestic travel to portfolio company locations.
- Compensation$180,000-$260,000
- Competitive equity package
Technology- TypeScript
- Python
- React
- SQL
- LLMs / Foundation Models
- Agentic Workflows
- Evals
- Snowflake
- Databricks
- Apache Iceberg
- Event-driven Systems
