The Role

A heavily funded software company is building a Forward Deployed Engineering team to deploy production AI directly into the businesses it operates.

This is not traditional solutions engineering.

You’ll work directly with GMs and operators, understand how their businesses run, identify the highest-leverage workflows to automate, and then build the actual software end-to-end.

That means owning everything from discovery through production:

• agents and LLM workflows

• prompts, evals and guardrails

• integrations and APIs

• backend systems

• React-based product surfaces

• SQL and data workflows

• deployment, monitoring and iteration

You’re not building demos or POCs that get handed off.

You’re shipping real systems into live operations and owning whether they actually improve the business.

What You’ll Do

• Embed with operating teams to understand messy, real-world business problems

• Identify the workflows where AI/software can create the most leverage

• Turn ambiguous operational problems into scoped technical solutions

• Build and deploy production-grade agentic systems end-to-end

• Work across Python/TypeScript, React and SQL

• Design evals, autonomy controls and human-in-the-loop workflows

• Integrate with existing systems and operational data

• Iterate with users after launch based on real production outcomes

• Work directly with senior operators and business leaders

• Turn successful deployments into reusable patterns that can scale across multiple businesses

What They’re Looking For

Ideally, you have 3–6 years of software engineering experience, with the strongest profiles typically in the 4–6 year range.

You should have:

• Strong full-stack engineering ability

• Experience with Python and/or TypeScript

• React experience

• Strong SQL/data fundamentals

• Experience shipping LLM or agentic systems into production

• Experience with evals, guardrails, tool use or autonomy controls

• Strong product judgment

• Comfort working directly with non-technical stakeholders

• Ability to take an ambiguous problem and own the solution from start to finish

Strong Backgrounds

Especially relevant backgrounds include:

• Forward Deployed Engineering

• Product Engineering

• Founding Engineering

• Full-Stack Engineering

• Applied AI Engineering

• Early-stage or high-growth startups

• Engineers who have worked at both a recognizable tech company and a startup

• Customer-facing engineers who have built and operated production software

Not a Fit If

This role is probably not the right fit if your experience is primarily:

• pre-sales or demo-focused solutions engineering

• internal prototypes without production ownership

• frontend-only or backend-only engineering

• research-focused AI without product delivery

• data annotation / AI training

• highly specialized Big Tech engineering with limited end-to-end ownership

Working Style

This is a high-autonomy environment.

You’ll be expected to operate like an engineer, product manager and technical operator at the same time — understanding the business problem, deciding what should be built, shipping it, and staying accountable for the outcome.

The role is based in Toronto and requires regular in-person work, along with travel to operating companies when needed.

Compensation

CA$180K–$260K base + equity

This is best suited to engineers who want broader ownership than a traditional SWE role and want to build AI systems against real operational problems rather than isolated technical features.