Senior Software Engineer

Department: Technology

Employment Type: Full Time

Location: Denver Headquarters

Compensation: $180,000 - $225,000 / year

Description

Project Canary is a climate technology company offering an enterprise data platform that helps energy companies improve and report on their emissions footprint. Project Canary builds high-fidelity sensors, ingests data from various other technologies and sources, and leverages proprietary analytics and models to deliver insights that operators can act on to reduce emissions. The data-driven technology enables energy operators to stop leaks faster, reduce risk, streamline reporting, and differentiate their operations for key stakeholders.

We’re hiring a senior engineer who enjoys solving hard technical problems and wants meaningful ownership in a growing company. 

This is a hybrid role based in downtown Denver, Colorado. We value in-person collaboration and build best when engineers spend meaningful time working side by side, whiteboarding, prototyping, and iterating together. 

WHAT YOU CAN EXPECT

• Ownership of meaningful systems with real influence over technical direction
• Direct access to product and company leadership
• Fast feedback loops and fewer layers between idea and implementation
• A collaborative environment where ideas are debated openly and decisions move quickly
• Visible impact. Your work will shape the trajectory of the company

WHAT “SENIOR” MEANS HERE In our environment, senior engineers:

• Make sound technical decisions and clearly explain the tradeoffs behind them
• Step into ambiguity and create clarity for others
• Deliver reliably and adjust execution based on business priorities
• Elevate the quality of systems, discussions, and team standards
• Contribute to a culture of curiosity, accountability, and momentum

WHAT WE LOOK FOR

Technical Depth and Rigor You have demonstrated the ability to reason through complex systems and make sound engineering decisions. That evidence might come from: 

• Designing and shipping production systems 
• Building products from 0 to 1 in ambiguous environments 
• Research, open-source contributions, or other technically rigorous work 
• Solving problems that required thoughtful system design, tradeoff analysis, or non-obvious technical decisions 

You are comfortable reasoning from first principles, when necessary, rather than relying solely on established patterns. We care more about how you think and build than whether your background follows a traditional path. 

Startup Adaptability We are a mid-stage startup. Priorities evolve. Documentation is not always perfect. Sometimes the best path forward is not immediately obvious. We are drawn to engineers who: 

• Thrive in environments with evolving structure 
• Take ownership of learning new systems and domains 
• Proactively identify next steps rather than waiting for assignments 
• Stay anchored to business goals, not just technical elegance 

Ownership, Pace, and Judgment Strong candidates demonstrate: 

• Clear reasoning behind architectural decisions 
• Ability to articulate tradeoffs, not just best practices 
• Awareness of business context when estimating timelines 
• The discipline to meet commitments 
• The judgment to increase intensity when the situation calls for it and to simplify when complexity is not justified 

We value engineers who understand that great software supports real business outcomes. 

Breadth and Curiosity We appreciate engineers who: 

• Have expanded their scope over time through new systems, domains, or increased responsibility 
• Are comfortable stepping slightly outside their core area when needed 
• See product, customer impact, and technical design as interconnected 

Deep specialists are welcome, especially those who have increased complexity and ownership within their domain. 

Experience That Is Particularly Relevant, Not Required Exposure to complex or real-world data problems is compelling, including: 

• Systems interacting with physical processes 
• Geospatial or spatial data 
• Combining multiple data streams to infer meaningful signals 
• Problems requiring modeling, interpretation, or non-obvious conclusions 

Strength in some areas can compensate for gaps in others. 

Benefits

• Salary range: $ annual base
• Hybrid work environment (at least 3 days/week in Denver office)<