Forward Deployed AI Engineer – System Test Automation

Infomatics Corp; Ottawa; On-site; CAD 110,000 - 150,000; Full time

Job summary

Infomatics Corp is seeking a Forward Deployed AI Engineer to accelerate real-world adoption of AI within end-to-end test automation. You will embed with system test engineers and development teams to adapt, harden and operationalize AI-driven workflows in production environments.

The role requires hands-on experience in software engineering or applied AI, strong Python skills, and ability to deploy AI solutions from prototype to real usage, while ensuring safety and guardrails are in place.

Qualifications

• 2+ years hands-on experience in software engineering or applied AI with ownership of deploying solutions into real environments.
• Proven ability to take AI or automation-based solutions from prototype to real-world usage including adapting to constraints, failures, and evolving requirements.
• Experience owning and troubleshooting AI behavior, tuning prompts/instructions, adding validation or guardrails, and diagnosing unsafe outputs.
• Experience working closely with engineers or end users to understand real workflows and iterate based on live feedback.

Responsibilities

• Forward deploy AI into Test Automation and turn AI prototypes into production-ready, repeatable solutions.
• Embed with system test and automation teams to understand workflows, constraints, and failure modes.
• Identify where AI can safely and effectively reduce manual effort.
• Adapt AI workflows to work with existing automation frameworks and real test data.

Skills

Python programming

Software engineering

AI deployment

Troubleshooting AI behavior

Workflow understanding

Tools

Qodo platform

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)