Principal Software Development Engineer - AI

Quarry Consulting; Canada; On-site; CAD 120,000 - 180,000; Full time

Job summary

Quarry Consulting is seeking a Principal Software Development Engineer - AI to own and shape our AI platform strategy remotely. You will design distributed systems, lead senior engineers, and mentor teams while coordinating with product and security functions.

This role focuses on architectural excellence across the stack and cross-team collaboration. You will balance make-vs-buy decisions, define platform boundaries between AI services and the broader product stack, and drive high-quality,

Qualifications

• Proven senior software engineer with staff-level impact.
• Experience designing production LLM/agentic systems at scale.
• Leadership in distributed systems and microservices architecture.
• Experience defining architecture standards adopted beyond own team.

Skills

Staff-level design

Distributed systems

DDD

Clean Architecture

Full-stack breadth

Python back-end

.NET experience

Architecture standards

Vendor evaluation

AI platform

Platform strategy

Security governance

Executive communication

Mentorship

Job description

Title: Principal Software Development Engineer - AI

Location: Remote - able to start 9am EST time

Duration: Permanent - Direct hire

Requirements:

• Professional software engineering experience with progressively increasing impact, including multiple years designing and operating production LLM/agentic systems at Staff-level scope or above.
• Proven technical leadership designing distributed systems and microservices for complex domains, with working knowledge of DDD and Clean Architecture principles applied to build highly performant, well-architected systems (prior DDD project experience not required).
• Full-stack breadth, spanning modern front-end frameworks and a Python back-end, sufficient to lead architecture across the entire product stack, not just AI services. .NET/C# experience is a plus, not a requirement.
• Track record of authoring architecture standards adopted beyond your own team, producing decision records that other senior engineers review, cite, and build on.
• Demonstrated quantified build-vs-buy decisions against named vendors (e.g., eval/observability platforms, vector stores), with cost models and explicitly rejected alternatives.
• Deep fluency in the current AI platform landscape: stateful agent orchestration, MCP and inter-agent (A2A) interoperability, eval-gated CI/CD, and vector-enabled persistence (PostgreSQL/pgvector, DiskANN-class indexing, managed offerings).
• A considered point of view on where the companies model strategy should be in two years, including whether and where to adopt fine-tuned small language models versus frontier APIs, grounded in cost, latency, and control tradeoffs.
• Experience defining platform boundaries between AI stacks and an existing product stack (e.g., Python AI services alongside .NET), including shared service-kit libraries other teams consume.
• Security and governance leadership: resource isolation, agentic workflow guardrails, responsible AI in a regulated, money-movement domain.
• Executive communication, articulating platform tradeoffs in terms leadership can act on, covering cost, risk, and optionality, not just engineering detail.
• A high degree of agency, building net-new systems and optimizing API performance where no established pattern exists, forging the path rather than waiting for one, with demonstrated ability to bring other engineers along that path.
• Demonstrated multiplier effect through mentorship: pairing with, unblocking, and growing senior engineers.
• A passionate and key contributor to the companies software factory, directing and reviewing agentic development while maintaining and improving our high quality and compliance bar.