Forward Deployed AI Engineer – System Test Automation

Infomatics Corp; Ottawa; On-site; CAD 90,000 - 130,000; Full time

Job summary

Infomatics Corp in Ottawa is seeking a Forward Deployed AI Engineer to accelerate real-world AI adoption within end-to-end system test automation. This role combines hands-on engineering with close collaboration with system test engineers, automation owners, and development teams to turn AI prototypes into reliable production-ready workflows.

You will embed with testing teams, adapt AI workflows to existing frameworks and real test data, and tune agentic AI components based on outcomes.

Qualifications

• 2+ years of hands-on software engineering or applied AI.
• Experience deploying AI/automation from prototype to production.
• Proven ability to tune AI behavior and add guardrails.
• Experience working with engineers and end users to iterate quickly.
• Strong Python programming and integration across systems.

Responsibilities

• Forward deployment of AI into test automation to production-ready solutions.
• Embed with system test and automation teams to understand workflows and failures.
• Identify where AI reduces manual effort and adapts to data and configurations.
• Extend AI workflows to work with existing automation frameworks and real test data.
• Collaborate with AI platforms to extend functionality and evaluation.

Skills

Python

AI Deployment

Troubleshooting

Collaboration

Productionization

Ownership

Job description

Only USC and GC candidates on W2. Telecom or Satellite Communications experience is mandatory.

We are seeking a Forward Deployed AI Engineer (FDE) to accelerate the real-world adoption of AI within our End-to-End System Test Automation. This role focuses on taking AI tools and prototypes and making them work reliably inside complex engineering environments. You will embed closely with system test engineers, automation framework/ test owners and development teams to adapt, harden and operationalize AI-driven workflows. This is a hands-on engineering role for individuals who thrive in ambiguity, enjoy working close to real users and can turn AI potential into measurable productivity gains.

Key Responsibilities

Forward Deployment of AI into Test Automation and turn AI prototypes into production-ready, repeatable solutions

Embed with system test and automation teams to:

Understand real testing workflows, constraints, and failure modes

Identify where AI can safely and effectively reduce manual effort

Adapt AI workflows to work with:

Existing automation frameworks

Real test data, schemas, and configurations

Agentic AI Implementation & Tuning

Implement and customize agentic AI workflows that:

Interpret requirements, schemas, or models

Assist in generating structured test assets

Tune AI behavior based on:

Real test outcomes

Failure analysis and feedback

Debug and resolve AI issues in live engineering environments

AI Tooling & Platform Feedback

Work with AI platforms (e.g., Qodo or similar) to:

Extend functionality where needed

Configure prompts, workflows, and validation layers

Evaluate emerging AI tools and frameworks in real system test contexts

Feed practical insights back to platform and leadership teams:

What works

What fails

What should scale

Enablement, Documentation & Guardrails

Document AI usage patterns and best practices

Safety-critical configurations

Invalid or destructive AI-generated outputs

Enable test engineers to adopt AI confidently and responsibly

Required Qualifications

• 2+ years of hands-on experience in software engineering or applied AI, with clear ownership of deploying solutions into real engineering or production environments
• Demonstrated experience taking an AI or automation-based solution from prototype to real-world usage, including adapting it to real constraints, failures, and evolving requirements
• Proven ability to own and troubleshoot AI behavior, tuning prompts/instructions, adding validation or guardrails, and diagnosing incorrect, unsafe, or low-quality outputs
• Experience working closely with engineers or end users to understand real workflows and iterating rapidly based on live feedback and outcomes
• Strong hands-on programming skills (Python required), with experience building orchestration, integration, or control logic across multiple systems

Preferred Qualifications

• Networking fundamentals (TCP/IP, MPLS, gNMI, YANG)