Forward Deployed AI Engineer – System Test Automation

Infomatics Corp; Ottawa; On-site; CAD 120,000 - 150,000; Full time

Job summary

Infomatics Corp in Ottawa is seeking a Forward Deployed AI Engineer to accelerate real-world adoption of AI in End-to-End System Test Automation. You will turn AI tools and prototypes into reliable, production-ready workflows that fit complex engineering environments.

This hands-on role requires collaborating with system test engineers and development teams to embed AI into existing automation frameworks, adapt prompts, and ensure safe, measurable productivity gains.

Qualifications

• 2+ years of hands-on software engineering or applied AI experience deploying solutions into real engineering or production environments.
• Experience turning AI/automation prototypes into production-ready workflows, adapting to real constraints and evolving requirements.
• Proven ability to own and troubleshoot AI behavior, tuning prompts and validation layers, diagnosing unsafe outputs.
• Experience collaborating with engineers or end users to understand real workflows and iterate based on live feedback.

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 workflows, constraints, and failure modes.
• Identify where AI can safely reduce manual effort and integrate with existing automation frameworks and real test data.

Skills

Python programming

Hands-on engineering experience

Problem solving

Tools

Python

Test Automation frameworks

Qodo

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)