Staff Software Engineer – AI & Platform (Freelance)

Alygra Advisory•Quebec, QC

22h

About The Position

We are supporting a high-growth digital consumer business in the search for a Staff Software Engineer (Freelance) to help shape the next phase of its engineering organization. This is a senior individual-contributor role combining technical leadership, hands-on engineering, platform architecture and AI enablement. You will work closely with engineering leadership and experienced developers to define how AI becomes embedded into the software development lifecycle — from developer tooling and workflows to agentic systems and automation. At the same time, you will contribute to the architecture and reliability of a large-scale consumer platform handling significant traffic and complex distributed workloads. The environment requires someone comfortable operating beyond clearly defined tickets and specifications. You will be expected to identify important technical problems, determine the right approach, align stakeholders and contribute directly to implementation.

Requirements

10+ years of professional software engineering experience, including significant experience designing and building scalable systems.
Approximately 6+ years working with distributed systems, platform architecture or similarly complex technical environments.
Previous experience operating at Staff Engineer, Principal Engineer, Technical Lead or an equivalent level of technical influence.
Demonstrated experience designing technical roadmaps and making architectural decisions across multiple systems or engineering teams.
Strong hands-on engineering skills — this is not an architecture-only or management position.
Experience working with high-traffic or high-scale digital platforms where reliability, performance and availability are critical.
Practical experience introducing or scaling the use of AI within engineering teams.
Experience influencing engineers across multiple teams without relying on direct management authority.
Strong understanding of the trade-offs between engineering, product, security and compliance.
Experience with platform engineering, developer experience (DX), internal tooling or shared engineering infrastructure.
Experience creating reusable libraries, frameworks or tools that improve engineering productivity and software quality.
Strong communication skills and the ability to bring structure to technically ambiguous problems.

Nice To Haves

AI-assisted software development and developer tooling.
Internal AI tools, integrations, plugins or engineering utilities.
AI-enabled development, testing or operational workflows.
Agentic architectures and multi-step AI workflows.
Autonomous or semi-autonomous agents.
Developer productivity and AI adoption programs.
Experience with technologies similar to: JavaScript / TypeScript, React, Next.js, Node.js, AWS, Distributed and cloud-native architectures, Modern AI development tools and frameworks.
Comfortable operating within a modern JavaScript/TypeScript and cloud-based environment.

Responsibilities

Define technical direction, including establishing and executing technical strategy across platform architecture, developer experience and AI-enabled engineering.
Translate broader engineering objectives into practical roadmaps, architectural decisions and technical standards.
Identify technical gaps, dependencies and risks that could limit scalability, reliability or engineering velocity.
Influence architecture across multiple engineering teams while remaining actively involved in implementation.
Accelerate AI-enabled engineering by evolving engineering practices toward an AI-native development model.
Identify opportunities to integrate AI into development, testing, debugging, documentation and operational workflows.
Design or implement internal tools, integrations, plugins and reusable capabilities that improve how engineers work with AI.
Explore and implement agentic workflows and autonomous engineering systems where they provide measurable value.
Establish practical standards and guardrails for effective and responsible AI usage within engineering.
Coach engineers on incorporating AI effectively into their daily workflows.
Strengthen platform engineering by working on complex technical challenges related to scale, performance, reliability and distributed systems.
Improve platform capabilities and internal tooling used by engineering teams.
Develop reusable libraries, frameworks and infrastructure that improve developer experience and software quality.
Investigate systemic or high-impact technical issues and drive them through resolution.
Help teams make pragmatic architectural decisions that balance scalability, security, product requirements and delivery speed.
Raise the engineering bar by partnering with engineers across teams through technical reviews, architecture discussions, pairing and coaching.
Introduce patterns and practices that improve maintainability, reliability and development velocity.
Act as a senior technical partner to engineering leadership.
Take ownership of ambiguous, cross-functional technical initiatives from problem definition through implementation.