Senior Engineer, AI Native SDLC

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Requisition

Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.

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.

• Design, build, and deploy core AI‑Native SDLC capabilities
  , including:
• Guidelines, standards and procedures
• Knowledge and technical knowledge of MCP servers with enterprise-grade security (authentication, authorization, auditability).
• Build and maintain secure Git Hub Actions workflows to run AI agents with controlled permissions and artifact handling.
• Define and own the AI‑Native SDLC framework
  , covering:
• AI‑assisted requirements, design, coding, testing, and operations
• Defining IDEs/Skills and Dev Containers
• 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.
• Secure and responsible use of LLMs and agents
• Data privacy, access control, and model interaction
• Traceability and auditability of AI‑generated outputs
• Develop and maintain:
• AI usage guidelines and approved patterns
• 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, and implementation guides
• Reference architectures (C4 models, ADRs)
• Sample pipelines, templates, and reusable assets
• Lead enterprise rollout and adoption
  , including:
• Developer enablement sessions and workshops
• Contribution to internal portals and knowledge bases
• 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 (Dev Ex).
• Agents
• SDKs
• CLI tools
• CI/CD templates
• Enable standardized environments using dev Containers or codified dev environments
  .
• Evaluate and prototype emerging AI/engineering technologies.
• Continuously refine SDLC frameworks based on:
• Developer feedback
• Usage metrics
• Act as a technical thought leader in AI‑driven software engineering.

• 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 (Git Hub Copilot preferred), including packaging for reuse.
• Experience designing or integrating MCP servers with strong security and governance controls.
• Hands‑on experience with Git Hub 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 Dev Ops practices
  .
• Strong ability to document frameworks and drive adoption across engineering teams
  .
• Working knowledge of architecture design artifacts (C4 diagrams, ADRs).
• Experience implementing scorecard-…