Artificial Intelligence Engineer

LanceSoft, Inc.

Montreal (administrative region)

On-site

CAD 80,000 - 110,000

Full time

14 days+

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Job summary

LanceSoft, Inc. is seeking a candidate for an internal ISG Architecture role in Montreal, focused on the development and evolution of governance, risk, and analysis tooling. The ideal candidate will work hands-on with internal teams to build tools for governance and risk management, utilizing AI coding assistants. This role emphasizes internal development over delivery, adapting governance to the demands of GenAI. Responsibilities include developing internal utilities and facilitating data integration, ensuring a flexible yet audit-safe architecture.

Qualifications

  • Experience in building tools and services for internal architecture.
  • Familiar with AI coding assistants and governance risk.
  • Ability to work with structured, semi-structured and unstructured data.

Responsibilities

  • Build and evolve internal architecture tooling.
  • Support GenAI intake and triage processes.
  • Design tools to surface risk signals early.

Skills

Build small services, scripts, CLIs, and internal utilities
Comfortable with REST APIs, JSON, async workflows
Systems and data integration mindset
Secure handling of credentials and sensitive internal data

Job description

This role is an internal ISG Architecture development and enablement role, focused on building and evolving architecture governance, risk, and analysis tooling used by ISG Architecture and its partner teams across Super Departments.

The “Forward Deployed” aspect refers to deep, hands‑on engagement with internal stakeholders and architecture processes, not client products or external delivery. The outputs of this role are internal tools, platforms, patterns, and governance mechanisms, not customer‑facing applications.

This role exists to help the architecture function adapt governance to the speed and volatility introduced by GenAI, while remaining audit‑safe, principled, and scalable.

Must Have
  • Build small services, scripts, CLIs, and internal utilities
  • Comfortable with REST APIs, JSON, async workflows
  • Can connect backend logic to lightweight UIs, notebooks, portals, or CLIs
  • Systems and data integration mindset
  • Pull data from APIs, documents, tickets, repositories, and architecture artifacts
  • Combine structured, semi-structured, and unstructured inputs
  • Secure handling of credentials and sensitive internal data
Expected
  • Heavy, responsible use of AI coding assistants
  • Strong human‑in‑the‑loop discipline
  • Reviews and validates AI‑generated output
  • Uses AI to accelerate thinking and execution, not replace judgment
  • Pragmatic use of LLMs for governance enablement
  • Surfacing governance signals and inconsistencies
  • Assisting with evidencing and analysis, not making autonomous decisions
  • Architecture, Governance & Risk Awareness
Elevated
  • Solid understanding of: Architecture principles, standards, patterns, and guardrails

The intent behind governance controls:

  • Where flexibility is appropriate
  • Where evidencing and rigor are non‑negotiable
  • Adaptive Governance & Risk Thinking
Awareness of multiple risk dimensions relevant to GenAI
  • Model and data risk
  • Security and privacy
  • Vendor dependency and lock‑in
  • Regulatory and audit sensitivity
Able to reason about risk‑based governance, including
  • Team and capability maturity
  • Scale and blast radius
  • Novelty versus precedent patterns
Designs tools that
  • Surface risk signals early
  • Escalate only when defined thresholds are exceeded
Governance Tooling & Enablement Responsibilities
  • Build and evolve internal architecture tooling that supports:
  • GenAI intake, triage, and readiness assessment
  • Architecture pattern alignment and deviation detection
  • ADR creation, analysis, and comparison
  • Architecture evidencing and audit support
  • Exception tracking and learning loops for governance improvement
Governance is delivered through
  • Tooling and automation
  • Embedded guardrails “not through heavyweight process alone.”
What Makes This Role Distinct
  • Embedded within ISG Architecture, not a delivery team
  • Uses engineering to scale governance capability
  • Enables many internal partner teams without owning external products
  • Continuously adapts governance mechanisms to GenAI’s pace of change
What This Role Is Not
  • Not a delivery or implementation role
  • Not traditional centralized architecture review only
  • It is an internal architecture enablement and development role, focused on making governance faster, smarter, and more adaptive through engineering
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