Senior Engineer, AI Native SDLC

United States Digital Space LLC

Toronto

On-site

CAD 130,000 - 180,000

Full time

14 days+

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Benefits offered by this job

Inclusive culture and perks
Tuition assistance

Job summary

United States Digital Space LLC is seeking a Senior Engineer/Senior Manager to own and scale our AI-Native SDLC across the company. You will lead the definition of standards, governance, and tooling while building secure, production-ready AI capabilities embedded throughout software delivery.

You will drive enterprise rollout, developer enablement, and reference implementations, partnering with Risk, Security, and Compliance to ensure safe adoption at scale.

Qualifications

  • 7+ years of hands-on software engineering experience.
  • Experience defining or implementing SDLC frameworks at scale.
  • Hands-on experience integrating with LLM APIs in production.
  • Experience building custom agents and agent skills for CLI-based harnesses.
  • Strong coding in TypeScript/JavaScript or Python; shell scripting is a plus.
  • Experience building RAG systems end-to-end.
  • Experience designing or integrating MCP servers with security controls.
  • Hands-on with GitHub Actions and secure AI agents in workflows.
  • Experience defining engineering policies, standards, or governance.
  • Solid understanding of cloud, APIs, distributed systems, and DevOps.

Responsibilities

  • Design, build, and scale AI-Native SDLC capabilities and tooling.
  • Own SDLC standards, governance, and documentation.
  • Lead enterprise rollout and developer enablement sessions.
  • Develop reference implementations and reusable templates.
  • Partner with Risk, Security, and Compliance to align with regulations.
  • Produce playbooks, patterns, and ADRs for AI workflows.
  • Drive adoption across engineering teams and maintain DevEx quality.

Skills

Software engineering
SDLC frameworks
LLM API integration
CLI tooling
TypeScript/JavaScript
Python
RAG systems
MCP servers security
GitHub Actions
Cloud (Azure)
DevOps
Documentation

Tools

Docker
Kubernetes
devContainers
GitHub Actions

Job description

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 the company.

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.

Is this role right for you? In this role, you will:
  • Hands‑On Engineering & Platform Build: Design, build, and deploy core AI‑Native SDLC capabilities, including:
    • Guidelines, standards, and procedures.
    • CLI‑based developer tooling (e.g., GitHub Copilot harnesses).
    • End‑to‑end RAG systems (ingestion, retrieval, grounding, evaluation).
  • 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.
AI‑Native SDLC Framework Ownership
  • Define and own the AI‑Native SDLC framework, covering:
    • AI‑assisted requirements, design, coding, testing, and operations.
    • Defining IDEs/Skills and DevContainers.
    • 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.
Policy, Standards & Governance
  • 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/auditability of AI‑generated outputs.
  • Develop and maintain engineering standards documentation, AI usage guidelines, approved patterns, and secure coding and review standards for AI workflows.
  • Partner with Risk, Security, and Compliance to ensure alignment with enterprise and regulatory requirements.
Process Documentation & Enterprise Rollout
  • Create clear, consumable documentation for the AI‑Native SDLC, including playbooks, patterns, 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, and scorecard‑based assessments to track adoption, compliance, and effectiveness with traceable evidence.
Developer Experience & Enablement
  • Build tooling and frameworks that improve developer productivity and experience (DevEx).
  • Package reusable components: agents, SDKs, CLI tools, CI/CD templates, and enable standardized environments using devContainers or codified dev environments.
Continuous Improvement & Innovation
  • Evaluate and prototype emerging AI/engineering technologies.
  • Continuously refine SDLC frameworks based on developer feedback, usage metrics, risk assessments, and act as a technical thought leader in AI‑driven software engineering.
Do you have the skills that will enable you to succeed in this role? We'd love to work with you if you have:
  • 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‑Have Qualifications
  • 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.
What's in it for you?
  • We strive to create an inclusive culture where every employee is empowered to reach their fullest potential, respected for who they are, and are embraced through bias‑free practices and inclusive values across the company.
  • We value the unique skills and experiences each individual brings to the bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone.
  • 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 and coffee, universal washrooms, and space for team collaboration.
  • Community engagement opportunities wherever you choose to work from.

Location(s): Canada : Ontario : Toronto

If you require accommodation during the recruitment and selection process, please let our Recruitment team know.

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