Transformation Engineer - Software Development, AI & Quality Engineering

About the role

The Transformation Engineer will design and build scalable engineering solutions that use AI and automation to improve software delivery, testing, and platform reliability. They will develop production-grade frameworks, services, and utilities in Python and related technologies to support intelligent validation, automation, and quality controls. The role involves partnering with engineering teams to embed quality engineering and validation practices early in the development lifecycle and driving shift-left transformation.

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.

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.

Qualifications

• Strong understanding of how intelligent test orchestration supports DevOps and continuous quality gates.
• Familiarity with AI-based approaches for data quality assurance including model validation, drift detection, or intelligent checks.
• Able 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.

Skills

• Python programming skills.
• Experience with CI/CD and DevOps practices.
• Knowledge of SQL and relational databases.
• Experience with modern automation and quality tools.
• Understanding of intelligent test orchestration and DevOps practices.
• Ability to apply AI/ML techniques in engineering workflows.

Benefits

Impactful work – Build and improve high-quality platforms used by analysts worldwide, with direct visibility into how your engineering solutions enhance reliability, trust, and production readiness.

Modern Engineering stack – Work with Python-based frameworks, CI/CD pipelines, AWS, Kubernetes, modern automation tools, and AI-assisted engineering and quality solutions.

Continuous learning – Grow through training, certifications, conferences, and clearly defined career paths into senior engineering and transformation roles.

Flexible environment – Work from our Chicago or Toronto office with hybrid flexibility, competitive compensation, comprehensive benefits, and strong work-life balance.

Innovation-driven culture – Experiment with AI-enabled engineering approaches, intelligent automation, and modern quality practices while helping shape technical strategy across platforms.

Pay

Expected base pay rates for the role will be between $130,000 and $150,000 per year. Actual salaries will be determined on an individualized basis and may vary based on factors including but not limited to education, training, experience, past performance, and other job-related factors.

Schedule

Hybrid work schedule available.