Senior Engineer, AI Native SDLC

Scotiabank • Toronto, ON

5d • Onsite

About The Position

The Senior Engineer / Senior Manager is a hands on technical leader and SDLC owner responsible for building, defining, and scaling an AI Native Software Development Lifecycle (SDLC) across Scotiabank. This role combines deep engineering execution with ownership of SDLC standards, policies, and frameworks, ensuring AI capabilities are embedded safely, consistently, and effectively across all stages of software delivery. The incumbent will lead through implementation, shaping enterprise standards by building real systems, while also formalizing governance, documentation, and rollout strategies that enable adoption at scale.

Requirements

• 7+ years of hands-on software engineering experience, with a strong emphasis on building and delivering systems.
• Demonstrated experience defining or implementing SDLC frameworks, standards, or engineering practices at scale.
• Hands-on experience integrating with LLM APIs in production use cases.
• Experience building custom agents and agent skills for CLI-based harnesses (GitHub Copilot preferred), including packaging for reuse.
• Strong coding expertise in TypeScript/JavaScript or Python; shell scripting is a strong asset.
• Experience building RAG systems end-to-end (ingestion → retrieval → grounding → evaluation).
• Experience designing or integrating MCP servers with strong security and governance controls.
• Hands-on experience with GitHub Actions, including secure execution of AI agents within workflows.
• Experience defining or contributing to engineering policies, standards, or governance frameworks.
• Solid understanding of cloud (Azure preferred), APIs, distributed systems, and DevOps practices.
• Strong ability to document frameworks and drive adoption across engineering teams.

Nice To Haves

• Working knowledge of architecture design artifacts (C4 diagrams, ADRs).
• Experience implementing scorecard-based reviews with measurable, traceable outputs.
• Experience with container platforms (Docker, Kubernetes).
• Hands-on use of devContainers or similar reproducible development environments.
• Experience contributing to developer platforms or internal engineering ecosystems.
• Experience in financial services or regulated environments.

Responsibilities

• Design, build, and deploy core AI-Native SDLC capabilities, including guidelines, standards, procedures, and CLI-based developer tooling (e.g., GitHub Copilot harnesses).
• Develop end-to-end RAG systems (ingestion → retrieval → grounding → evaluation).
• Implement knowledge and technical knowledge of MCP servers with enterprise-grade security (authentication, authorization, auditability).
• Build and maintain secure GitHub Actions workflows to run AI agents with controlled permissions and artifact handling.
• Write high-quality production code (TypeScript/JavaScript or Python) and contribute directly to shared platforms and repos.
• Define and own the AI-Native SDLC framework, covering AI-assisted requirements, design, coding, testing, and operations, and defining IDEs/Skills and DevContainers.
• Define integration patterns for AI across CI/CD pipelines.
• Translate strategy into working reference implementations and reusable templates.
• Ensure the SDLC is practical, developer-friendly, and grounded in real tooling.
• Define formal SDLC policies, engineering standards, and guidelines for AI-enabled development.
• Establish guardrails for secure and responsible use of LLMs and agents, data privacy, access control, model interaction, and traceability and auditability of AI-generated outputs.
• Develop and maintain engineering standards documentation, AI usage guidelines and approved patterns, and secure coding and review standards specific to AI workflows.
• Partner with Risk, Security, and Compliance to ensure alignment with enterprise and regulatory requirements.
• Create clear, consumable documentation for the AI-Native SDLC, including playbooks, patterns, implementation guides, reference architectures (C4 models, ADRs), and sample pipelines, templates, and reusable assets.
• Lead enterprise rollout and adoption, including developer enablement sessions and workshops, contribution to internal portals and knowledge bases, and hands-on support for early adopter teams.
• Define and implement scorecard-based assessments to track adoption, compliance, and effectiveness with traceable evidence.
• Build tooling and frameworks that improve developer productivity and experience (DevEx).
• Package reusable components: Agents, SDKs, CLI tools, CI/CD templates.
• Enable standardized environments using devContainers or codified dev environments.
• Evaluate and prototype emerging AI/engineering technologies.
• Continuously refine SDLC frameworks based on developer feedback, usage metrics, and risk assessments.
• Act as a technical thought leader in AI-driven software engineering.

Benefits

• Upskilling through online courses, cross-functional development opportunities, and tuition assistance.
• Competitive Rewards program including bonus, flexible vacation, personal, sick days and benefits will start on day one.
• Free tea & coffee, universal washrooms, and lots of space for team collaboration.
• Opportunities for community engagement & belonging with our various programs.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed