Transformation Engineer - Software Development, AI & Quality Engineering

Fitch Group•Toronto, ON

21d•Hybrid

About The Position

Fitch Group is seeking a hands-on Transformation Engineer with strong expertise in software development, AI-enabled engineering, and modern quality practices. This role will focus on building intelligent engineering solutions that improve how teams design, develop, test, and deliver data-intensive platforms and applications. The ideal candidate is a strong developer who can apply AI, automation and engineering best practices to accelerate delivery, improve platform reliability, strengthen quality, and help evolve traditional QA into a more proactive, engineering-led quality model.

Requirements

8+ years of experience in software engineering, data platforms, ETL, or large-scale distributed systems.
Strong hands-on development experience, particularly in Python, with the ability to build reusable frameworks, services, and automation solutions.
Experience applying AI/ML or intelligent automation in engineering workflows, especially in validation, testing, optimization, or anomaly detection.
Strong knowledge of data systems, including ETL, batch/streaming pipelines, APIs, and microservices.
Advanced experience with SQL and relational databases such as Oracle and PostgreSQL.
Experience with modern automation and quality tools, including Playwright and/or Selenium, with a strong understanding of how quality engineering supports software delivery.
Familiarity with CI/CD, DevOps, and continuous quality engineering practices.
Demonstrated ability to influence teams to adopt quality‑first and shift‑left practices across design, development, and deployment.
Familiarity with self-healing automation, intelligent orchestration, or AI-assisted validation frameworks.

Nice To Haves

Strong understanding of how intelligent test orchestration supports DevOps and continuous quality gates.
Familiarity with AI‑ or ML‑based approaches for data quality assurance including model validation, drift detection, or intelligent checks.
Ability to act as a thought partner on how AI can continuously improve engineering and quality outcomes across platforms.
Awareness of AI governance, explainability, and responsible AI principles, particularly in regulated or risk‑sensitive environments.
Financial Services Background – Experience with analytical workflows, financial products, or regulatory processes

Responsibilities

Design and build scalable engineering solutions that use AI and automation to improve software delivery, testing, and platform reliability.
Develop production-grade frameworks, services, and utilities in Python and related technologies to support intelligent validation, automation, and quality controls.
Partner with engineering teams to embed quality engineering and validation practices early in the development lifecycle and drive shift-left transformation.
Apply AI/ML techniques to improve test generation, coverage optimization, anomaly detection, defect identification, and engineering insight.
Build and enhance data and platform validation capabilities across ETL pipelines, APIs, microservices, and streaming architecture.
Integrate automation and intelligent quality checks into CI/CD pipelines to support continuous testing, quality gates, and release confidence.
Help modernize legacy QA approaches into developer-aligned quality engineering frameworks and scalable engineering practices.
Collaborate across Technology, Risk, Compliance, Operations, and Emerging Tech to drive consistent engineering and quality outcomes.
Provide clear reporting and insights on engineering quality, risks, and release readiness, leveraging AI where appropriate.