As a Staff Product Engineer, you will lead the development of AI-driven products, mentor engineers, drive efficiencies, and establish architectural standards across teams.
The Opportunity
Join Sitetracker as a Staff Product Engineer and play a pivotal role in shaping the future of enterprise software by harnessing cutting-edge AI. You'll provide the technical acumen to deliver best-in-class software solutions, relentlessly focused on quality and efficiency, leveraging AI to dramatically increase development velocity and throughput. This is a unique opportunity to apply legitimate AI for commercial use, combining established excellence with a pioneering spirit to deliver breakout solutions with outsized impact.
What You'll Do
As a Staff Product Engineer, you will provide high-level technical leadership and architectural vision for our groundbreaking new AI harness solution. You will own complex solutions end-to-end, actively steering your team away from traditional SaaS paradigms and into building highly scalable, high-throughput AI infrastructure. This role demands a proactive problem-solver who can break down complex challenges into iterative solutions, ensuring alignment with stakeholders every step of the way. You will work across multiple teams to deliver scoped work, constantly finding ways to unblock yourself and others, ultimately solving big problems that enhance the efficiency of the entire Engineering organization.
The Skills You'll Have
Leadership & Team Enablement
* Proactively mentor Senior and Mid-level engineers, fostering growth and development.
* Hold your team accountable for delivering high-quality, efficient solutions.
* Effectively resolve technical disputes and drive engineering consensus.
* Proactively identify and mitigate cross-team dependencies to unblock progress.
* Establish new engineering standards for AI development that elevate the entire organization.
Technical Expertise & Architecture
* Design and successfully deploy complex, AI-driven product capabilities end-to-end.
* Write highly scalable and efficient code for our core AI harness.
* Securely handle and integrate Large Language Models (LLM) and other AI components.
* Design fault-tolerant systems that seamlessly orchestrate multiple AI agents.
* Take absolute end-to-end accountability for solutions, from concept and architecture to monitoring and maintenance.
Quality & Customer Focus
* Deeply understand customer challenges and the value your team's AI solutions bring.
* Implement robust testing strategies for non-deterministic AI outputs.
* Ensure stringent data privacy guardrails are built into all AI systems.
* Architect automated evaluation pipelines to continuously assess AI output quality.
* Anticipate and unlock new, unprompted business value for customers through innovative AI harness applications.
Communication & Influence
* Confidently defend complex architectural and technical choices.
* Drive alignment and foster collaboration across Product and Engineering teams.
* Present complex AI concepts clearly to diverse audiences, from engineers to executives.
* Evangelize the technical vision of our AI harness both internally and externally.
* Directly influence the overall product roadmap by identifying and leveraging emerging AI capabilities.
Within 90 Days, You'll
- Establish the foundational architectural vision for your team's AI solutions.
- Begin delivering your first end-to-end AI-driven product capabilities, focusing on quality and efficiency.
Within 180 Days, You'll
- Lead the successful delivery of multiple complex AI-driven product capabilities, driving alignment across product and engineering.
- Drive engineering consensus and proactively resolve technical deadlocks, contributing significantly to team output.
- Contribute to defining and establishing best practices that begin to uplevel the entire engineering team, especially around secure and scalable AI development.
Within 365 Days, You'll
- Solidify the architectural foundation for your team, ensuring scalability, security, and fault tolerance for our AI harness that unblocks other engineers.
- Consistently deliver innovative, end-to-end AI-driven product capabilities that significantly increase velocity and throughput across the organization.
- Uplevel the entire engineering organization by establishing and propagating best practices, standards, and mentorship in AI development and complex problem-solving.
Top Skills
AI
Large Language Models
Software Development
Similar Jobs
Fintech • HR Tech
The Staff Software Engineer will architect and build solutions for Gusto's product suite, mentor engineers, and collaborate with cross-functional teams to enhance customer experiences.
Top Skills:
JavaScriptReactRuby On Rails
Software
The Staff High-Speed Analog ASIC Product Engineer designs specifications for Analog ASICs in datacenter products, collaborates with teams on product definition, and analyzes performance data for improvements.
Top Skills:
Analog CircuitsAsicStatistical Analysis
Big Data • Cloud • HR Tech • Payments • Software
Build and maintain complex customer-facing features, support other engineers, and take ownership of technical decisions while collaborating with Product and Design teams.
Top Skills:
.NetAzureAzure SqlNode.jsPostgresReactTypescript
What you need to know about the Montreal Tech Scene
With roots dating back to 1642, Montreal is often recognized for its French-inspired architecture and cobblestone streets lined with traditional shops and cafés. But what truly sets the city apart is how it blends its rich tradition with a modern edge, reflected in its evolving skyline and fast-growing tech industry. According to economic promotion agency Montréal International, the city ranks among the top in North America to invest in artificial intelligence, making it le spot idéal for job seekers who want the best of both worlds.
Key Facts About Montreal Tech
- Number of Tech Workers: 255,000+ (2024, Tourisme Montréal)
- Major Tech Employers: SAP, Google, Microsoft, Cisco
- Key Industries: Artificial intelligence, machine learning, cybersecurity, cloud computing, web development
- Funding Landscape: $1.47 billion in venture capital funding in 2024 (BetaKit)
- Notable Investors: CIBC Innovation Banking, BDC Capital, Investissement Québec, Fonds de solidarité FTQ
- Research Centers and Universities: McGill University, Université de Montréal, Concordia University, Mila Quebec, ÉTS Montréal
