Role: Lead Forward Deployed Engineer
Location: Vancouver, BC preferred | Ontario, Canada – Remote
Type: Full-Time
Travel: 15–20%
Salary Range: 140k 170k (CAD)
We are looking for a Lead Forward Deployed Engineer who combines strong hands-on software engineering with enterprise customer-facing experience. You will work directly with customers to understand their technical challenges, lead discovery, design AI solutions, and build and deploy them into production.
Key Responsibilities
- Lead technical discovery sessions with enterprise customers, architects, engineering, and business teams.
- Understand customer workflows, data flows, security requirements, and technical challenges.
- Design, build, and deploy production LLM, RAG, and agentic AI solutions.
- Develop integrations with enterprise APIs, data sources, ERPs, and document-management systems.
- Lead architecture reviews, customer workshops, and production onboarding/deployment.
- Implement evaluation, guardrails, monitoring, and observability for AI systems.
- Partner with Product and Core Engineering to turn recurring customer needs into platform capabilities.
Must-Have
- Strong production software engineering experience with Python or TypeScript/Node.js.
- Hands-on experience building and deploying production LLM, RAG, and agentic AI solutions.
- 3+ years of direct customer-facing technical experience, working with enterprise customers, engineering teams, architects, or business stakeholders.
- Proven experience leading technical discovery, customer workshops, requirements gathering, and production solution delivery.
- Ability to understand customer problems, translate them into technical solutions, and personally build and deploy those solutions.
- Experience with AWS, Azure, or GCP, Docker, databases, and REST/GraphQL APIs.
- Strong communication and presentation skills.
- Willingness to travel 15–20%.
Nice to Have
- Computer vision, multimodal AI, or document parsing.
- Technical drawings, blueprints, scanned documents, or complex document processing.
- Neo4j, knowledge graphs, or Graph RAG.
- Multi-agent systems.
- Industrial, manufacturing, energy, procurement, or enterprise AI experience.
