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.

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