Forward Deployed Engineer (FDE) — AI / Agentic Software

🚀 We’re Hiring: Forward Deployed Engineer (FDE) — AI / Agentic Software

📌 POSITION DETAILS

**📍 Locations: Toronto, Canada**

🏢 Work Model: Hybrid

📅 Office Requirement: Minimum 3 days/week — 4 days preferred

💼 Employment: Full-time

🎯 Experience: 3–6 years

💰 Base Salary: $185,000+ Base

📈 Equity: Competitive equity

✈️ Travel: 2–3 days/week to portfolio company locations

🌎 Visa: H-1B transfers, OPT transfers & relocation supported

👥 Hiring: Multiple openings

About the Opportunity

We’re looking for Forward Deployed Engineers who can operate at the intersection of software engineering, AI, product, and business operations .

This is a highly hands-on, Palantir-style FDE opportunity within a software holding company . You will work directly with portfolio companies, understand their operational challenges, identify high-impact opportunities for AI and agentic automation, and then build, deploy, operate, and improve production systems end-to-end .

This is not a presentation-heavy solutions role . You will be expected to write production code, work directly with operators and executives, and take ownership of measurable outcomes.

What You’ll Do

🔹 Embed with portfolio companies

• Work directly with portfolio companies to understand their operating models, workflows, and business priorities.
• Build relationships with GMs and operational leaders and quickly earn their trust.
• Identify the 2–3 highest-leverage workflows where agentic software can create meaningful impact.

🔹 Build and deploy AI-powered solutions

• Design and build the initial “wedge” for each deployment.
• Develop integrations, prompts, evaluations, UI surfaces, and agentic workflows.
• Launch the first production agentic loop using the organization’s core platform.
• Own the entire technical delivery cycle rather than handing work between specialized teams.

🔹 Operate systems after launch

• Monitor and tune deployed systems in production.
• Adjust autonomy levels and gating based on real-world performance.
• Track outcomes and continuously improve deployed workflows.
• Transition stable solutions to portfolio operations teams when appropriate.

🔹 Act as the technical partner to business leaders

• Serve as the technical face of the organization to portfolio company GMs.
• Translate ambiguous operational challenges into clearly scoped technical solutions.
• Set expectations, communicate trade-offs, and ensure stakeholders understand the value created by the system.

🔹 Build reusable organizational knowledge

• Bring lessons from deployments back to HQ.
• Identify recurring patterns across companies and verticals.
• Codify successful approaches into reusable playbooks.
• Help accelerate future deployments by turning individual solutions into repeatable systems.

Required Technical Skills

You should be comfortable owning a production system from backend through frontend and data layer .

Core requirements:

• Strong full-stack engineering capability.
• TypeScript or Python for backend development.
• Strong React experience.
• Strong SQL proficiency.
• Ability to independently own end-to-end technical delivery.
• Experience programming with Go and/or TypeScript .
• Experience working with modern AI development tooling and coding agents.
• Strong understanding of LLMs / foundation models and agentic workflows.

AI / Agentic Engineering Experience

A major requirement is experience building real production AI systems , not simply experimenting with AI or creating demonstrations.

Strong candidates will have experience with:

• Production LLM applications
• Agentic workflows
• AI-powered automation
• Evaluation frameworks / evals
• Autonomy gating
• Outcome tracking
• AI developer tools and coding agents
• Integrations and workflow automation
• Production deployment and post-launch iteration

We are specifically looking for engineers who have shipped AI/agentic software to external users.

Business & Operator Mindset

Technical ability alone isn’t enough for this role.

You should be able to:

• Understand how a business operates.
• Read and interpret a P&L .
• Identify operational inefficiencies.
• Translate business problems into technical opportunities.
• Determine where AI can create the highest leverage.
• Work effectively with non-technical executives.
• Navigate ambiguity w…