Forward Deployed Engineer / Sr. SW Engineer (AI)

GuruLink; Toronto; Remote; CAD 120,000 - 160,000; Full time

Job summary

GuruLink is hiring Forward Deployed Engineers to bring an innovative enterprise-grade product into production. You will own the deployment journey from first process file to a functioning, improving system, collaborating with a global team across Java services and React interfaces.

You’ll measure performance, scale fault tolerance, and shape the product through direct customer feedback.

Qualifications

• Strong communications for a client-facing professional service level role.
• Strong software development fundamentals including functional programming concepts.
• Experience building production-grade AI products.

Responsibilities

• Deploy and own end-to-end journey from first process file to a running production workflow.
• Ensure at least one workflow is running with measurable performance gains by 90 days.
• Manage deployments for 3–5 customers within 12 months, building and improving agents and BPMN workflows.

Skills

Communications

Software development

AI in production

Education

Bachelor's degree or higher

Tools

Java

Scala

Rust

C++

Golang

Job description

Location: REMOTE / Toronto, Ontario This job allows you to work remotely.

About the role:

We have a new enterprise grade kind of product: business processes described in natural language, generated as executable BPMN workflows, and improved autonomously from production data. We’re hiring the first cohort of Forward Deployed Engineers to bring it into production at enterprise customers. You’ll own the deployment journey from first process file to a working, improving system, and hand off a functioning capability to the customer’s team. The code you write and the patterns you discover feed directly back into how the product is built. This is a rare opportunity to shape a product, a function, and a field practice from day one. You’ll work endtoend across Java services and React interfaces, collaborating closely with a talented global team to measure, improve, and scale performance and fault tolerance in real-world distributed systems.

Must haves:

1. 1) Strong communications skills, this is a client facing professional service level role.
2. 2) Strong Software development and design fundamental knowledge backed by many years of industry experience, including Functional programming concepts,etc.
3. 3) Experience building production grade AI products.

What You’ll Be Doing:

• Deploy and prove: own the end-to-end journey from first process file to a running, measurably improving production workflow.
• At 90 days: at least one workflow running, the improvement loop active, and measurable fitness gains the customer can see.
• At 12 months: 3–5 customers with viable deployments.
• Feed the product: You're building the product as you work with customers; this includes features, agents, and skill files. When you find a bug, you're empowered to fix it.
• Drive organisational adoption: work across technical and business stakeholders to turn early deployments into lasting customer capability
• Work at technical depth: configure clusters, debug integration failures, and build custom agents where platform defaults don’t fit
• Build the playbook: document what good looks like as you discover it and make the next deployment faster
• Hand off deliberately: leave each customer team trained, independent, and able to act on improvement results without you

Must Have Skills:

• Strong expereince with complied/Functional projgramming languages: ie: Java stack, Scala, RUST, C#, C++. or Golang, etc.
• Enterprise production experience: you’ve shipped something inside a large organisation and stayed to see it operate. You know why governance and resilience matter at scale.
• Technical depth: you can debug an integration failure, write a custom agent against a legacy API, stand up a cluster from scratch, and explain generated BPMN to both engineers and business leads.
• Stakeholder communication: you work effectively across engineering, architecture, and business leadership and adapt how you communicate without losing precision.
• Practical AI experience: you’ve used AI to solve real problems in production – not just experimented. You understand context management, prompt engineering, agent testing, and integration tradeoffs.
• Comfort with ambiguity: you make sound judgment calls without a playbook and document what you learn.
• Occasional travel may be required

Nice to Have Skills:

• Experience in a customer-facing engineering or professional services role.
• Familiarity with regulated industries such as financial services, healthcare, or insurance
• Production experience with agentic systems or AI-integrated workflows.
• Contributions to a shared platform or open source project that others built on.