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Infomatics Corp

Forward Deployed AI Engineer – System Test Automation

Ottawa, ON, Canada

Contract

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Job details

Job type: Contract
Apply by: Nov 6, 2026
Experience: 2+ years of hands-on experience in software engineering or applied AI, with clear ownership of deploying solutions into real engineering or production environments
Posting language: English
Posted: Oct 7, 2026

Original 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

Help define guardrails for:

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)
Linux, CI/CD, Docker, Kubernetes

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More about this job

Responsibilities

Deploy and adapt AI workflows for end-to-end system test automation, working closely with test engineers and development teams to make prototypes reliable in real engineering environments. Tune and troubleshoot agentic AI, provide feedback on AI platforms, document best practices, and establish guardrails for safe adoption.

Requirements

Requires at least two years of hands-on software engineering or applied AI experience, including deploying and owning AI or automation solutions in real-world environments. Candidates must have strong Python skills, experience tuning and validating AI behavior, and mandatory telecom or satellite communications experience; networking, Linux, CI/CD, Docker, and Kubernetes are preferred.

Skills

Python
Applied AI
Agentic AI Workflows
Software Engineering
Test Automation
Prompt Tuning
AI Validation And Guardrails
Troubleshooting
Systems Integration
Telecom
Satellite Communications
TCP/IP
MPLS
gNMI
YANG
Linux

Visa sponsorship

Not detected in the job text

Keywords

Forward Deployed Engineer
Artificial Intelligence
System Test Automation
Telecom
Satellite Communications
Python
Agentic AI
AI Workflows
Prompt Tuning
Test Assets
Test Data
Schemas
Automation Frameworks
AI Validation
Guardrails
Failure Analysis
Systems Integration
Qodo
TCP/IP
MPLS
gNMI
YANG
Linux
CI/CD
Docker
Kubernetes
Production Deployment
End-To-End Testing

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