Software Developer, AI Engineering & SDLC Transformation

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Software Developer, AI Engineering & SDLC Transformation based in Canada.

This is a hands-on software engineering role focused on transforming the software development lifecycle through generative AI and agentic technologies.
You’ll combine strong engineering fundamentals with modern AI capabilities to build practical solutions that improve developer productivity, software quality, and delivery speed.
Working across business, product, architecture, and engineering teams, you’ll identify opportunities to embed AI throughout the SDLC.
You’ll design reusable agentic workflows, developer tools, and engineering foundations that can operate securely within enterprise environments.
The role covers everything from requirements and architecture through development, testing, quality assurance, and traceability.
You’ll help establish scalable engineering practices around AI, including evaluation, observability, governance, security, and guardrails.
This is an opportunity to work at the intersection of software engineering, financial services, and rapidly evolving AI technologies in a collaborative environment.

• Partner with business, product, architecture, and engineering teams to identify high-value opportunities for AI-driven improvements across the software development lifecycle.
• Build and deploy AI-powered solutions that improve engineering productivity, software quality, developer experience, and delivery outcomes.
• Design and develop reusable agentic workflows, developer tools, and engineering foundations that can scale across teams and use cases.
• Implement capabilities for context retrieval, agent orchestration, tool integration, model evaluation, observability, guardrails, and secure execution.
• Apply generative and agentic AI to requirements gathering, solution design, architecture, software development, testing, quality assurance, defect analysis, and traceability.
• Develop AI-assisted testing and automated quality controls to improve reliability throughout the SDLC.
• Ensure AI-enabled engineering solutions align with enterprise security, privacy, governance, risk management, and compliance requirements.
• Evaluate AI models, agent frameworks, coding assistants, and developer technologies, recommending solutions appropriate for enterprise software engineering.
• Collaborate with development teams to pilot, refine, adopt, and scale AI-enabled engineering practices.
• Measure the effectiveness of AI initiatives using engineering productivity, quality, adoption, and developer experience metrics, continuously optimizing outcomes.
• Contribute to architecture reviews, engineering standards, technical documentation, and knowledge-sharing initiatives.

Requirements

• Degree in Computer Science, Software Engineering, Economics, Mathematics, or a related discipline, or equivalent practical experience.
• 2+ years of software development experience, ideally within financial services, investments, mutual funds, or a similarly regulated environment.
• Strong hands-on software engineering experience, particularly with Python, and demonstrated experience delivering production-ready software.
• Experience developing and supporting production APIs, services, and developer tools.
• Strong understanding of the full software development lifecycle and modern engineering practices.
• Hands-on experience with generative AI and agentic AI engineering, with practical experience applying emerging technologies to real-world engineering challenges strongly preferred.
• Experience with AWS, Snowflake, and Kubernetes.
• Familiarity with Java, JavaScript/TypeScript, or other enterprise programming languages is an asset.
• Strong knowledge of source control, APIs, microservices, containers, CI/CD, automated testing, Infrastructure as Code, and DevSecOps practices.
• Understanding of security, privacy, governance, and risk considerations associated with AI agents and enterprise systems.
• Experience with open-source or open-weight coding models, including model evaluation, serving, self-hosting, or integration into engineering workflows, is an advantage.
• AWS certification or equivalent hands-on cloud experience is considered an asset.
• Experience working in Agile or Scrum environments and applying modern DevSecOps practices is an advantage.
• Ability to quickly learn emerging AI models, agent frameworks, and development technologies and translate them into practical, scalable solutions.
• Strong communication, collaboration, and interpersonal skills, with the ability to work effectively across technical and non-technical teams.

Benefits

• Competitive total compensation: Annual base salary plus target discretionary performance bonus ranging from $101,000 to $118,000 , depending on experience and qualifications.
• RRSP contributions: Employer RRSP contributions after six months of employment, with no employee matching requirement.
• Fully remote work: 100% remote working arrangements within Canada.
• Comprehensive health coverage: Benefits effective from the first day, with 100% employer-paid premiums.
• Mental health support: Up to $5,000 annually for mental health services and therapy.
• Parental support: Parental leave top-up to 100% of salary for up to 25 weeks .
• Home office support: Up to $650toward home office equipment.
• Generous time off: Flexible vacation policies, including two paid volunteer days each year.
• Professional development: Access to more than 11,000 training and development courses , tuition reimbursement, and financial rewards for completing required professional designations.
• Inclusive workplace: Diversity and inclusion initiatives and active Employee Resource Groups.
• Career growth: Extensive opportunities for learning, development, and long-term career progression.
• People-focused culture: A supportive environment recognized among Canada's leading employers and workplaces.