Staff Software Engineer

Staff Software Engineer

Remote

Who We Are:

Digible is a privately owned and operated digital marketing company founded in 2017 with a mission to bring cutting-edge solutions to the multifamily industry. We offer a full suite of digital services, alongside Fiona, our predictive analytics platform—the first of its kind.

At Digible, we take pride in our collaborative, transparent, and authentic culture. Since 2021, we've been recognized as a Top Workplace in Colorado and secured the #8 spot in the Best Places to Work Multifamily rankings. From our hiring process to our All Hands meetings and Town Halls, our values are at the core of everything we do.

We believe diversity fuels innovation, and we strive to create an inclusive environment where everyone can bring their authentic selves to work. If you're ready to do the best work of your career, we'd love to have you on the team!

Core Values

• Authenticity - The commitment to be steadfast and genuine with our actions and communication toward everyone we touch.
• Curiosity - The belief that a deep and fundamental curiosity (the "why") in our work is vital to company innovation and evolution.
• Focus - The collective will to remain completely devoted and ultimately accountable to our deliverables.
• Humility - The recognition and daily practice that "we" is always greater than "I".
• Happiness - The decision to prioritize passion and love for what we do above everything else.

The Role:

As a Staff Software Engineer, you'll join Digible's Engineering team as a senior individual contributor who ships meaningful product work while helping evolve how our teams build software. Our Engineering team is moving toward an AI-native development model, where humans design, spec, and evaluate solutions while AI accelerates implementation.

In this role, you'll operate as a full-stack engineer across a modern, interconnected codebase while influencing technical direction, team practices, and AI-native development adoption. You may embed in one or more product pods, act as a technical lead within a pod, or partner across initiatives where ambiguity is high and the path forward needs to be shaped through hands-on work.

This role is built for someone who leads through execution. Your credibility will come from shipping, pairing, modeling strong practices, and helping teams sustain improvements after you step back. When the path is unclear, you step in. When others are ready to own it, you step back. Then you help drive the next meaningful improvement.

You'll Love This Job If You:

• Enjoy owning complex problems end-to-end, from customer need through production and team adoption.
• Thrive in dynamic, growth-stage environments where priorities shift, scope is fluid, and ambiguity is common.
• Are deeply excited about AI-native development and evolving how software is built.
• Like working closely with Product and Design as peers, holding customer context and technical context in the same conversation.
• Take pride in improving systems, practices, and team capability, not just individual features.
• Prefer shipping, learning, and iterating over waiting for perfect requirements.
• Enjoy mentoring, pairing, and transferring practices through hands-on collaboration.
• Want to influence technical direction without relying on formal authority.
• Find energy in modernizing and improving real production systems while keeping them stable.
• Like balancing speed with strong engineering standards, architectural judgment, and quality.

What You'll Do:

• Embed in key initiatives or pods and ship meaningful product features using advanced engineering practices.
• Think product-first by owning outcomes, not just tickets, and ensuring your work delivers real customer impact.
• Design, build, and ship features end-to-end, from problem definition through production.
• Use AI as a core part of your workflow, including writing specs, generating code, critically evaluating outputs, and improving development loops.
• Practice and model augmented coding while maintaining high standards for code quality, testing, system design, and deployment confidence.
• Pair with engineers inside their actual workflows to transfer practices through collaboration, not instruction.
• Drive ambiguous or high-impact problems when the path forward is unclear.
• Make thoughtful technical decisions with incomplete information and adjust when data or production reality points to a better path.
• Contribute across the full stack, including Node, TypeScript, React, SQL, and cloud-native services across AWS and GCP.
• Shape the technical foundation alongside feature work, including service boundaries, data flows, APIs, observability, reliability, and deployment practices.
• Debug complex issues across distributed systems and make architectural decisions that hold up beyond a single feature.
• Own production systems, including observability, reliability, deployments, postmortems, and on-call responsibilities.
• Improve and evolve large, interconnected production codebases with empathy for legacy systems and the teams that maintain them.
• Influence technical direction within your pod and contribute to broader engineering improvements across pods.
• Leave systems, practices, and teams better than you found them.

How Success Will Be Measured:

• You deliver high-quality, customer-impacting features from concept through production.
• You drive measurable improvements in team velocity, quality, reliability, AI-native development adoption, or engineering practices.
• You positively influence teams through mentorship, pairing, shared standards, and improved practices that continue after your direct involvement decreases.

What You Should Have:

• 10+ years of professional software engineering experience building and shipping products that matter.
• Deep fluency in at least one modern typed web stack. We use Node, TypeScript, React, and SQL; depth of judgment and ability to transfer skills matter more than an exact technology match.
• Strong systems thinking, including architectural judgment across domains, debugging across service boundaries, and sound decision-making under pressure.
• Experience owning services end-to-end, including build, deploy, run, monitoring, observability, on-call support, and postmortems.
• Familiarity with cloud environments such as AWS, GCP, or similar.
• Strong production instincts and experience making decisions that keep systems healthy over time.
• Legacy empathy and a thoughtful approach to modernizing large existing codebases while keeping production systems stable.
• Strong testing standards, including experience establishing or improving testing practices for teams.
• Ability to navigate and improve large, existing codebases quickly.
• Comfort working in ambiguous, fast-moving environments with shifting priorities, loose structure, and multiple hats.
• Strong communication skills, with the ability to translate between engineering depth, product needs, and business context.
• Experience collaborating cross-functionally with Product and Design as true peers.
• A product mindset, starting with the customer problem, challenging assumptions, and connecting technical decisions to business outcomes.
• Significant experience using AI tools to improve development workflows and outcomes, with concrete examples of faster delivery, higher quality, fewer handoffs, or fundamentally different workflows.
• A track record of mentoring, pairing, elevating other engineers, and influencing without authority.

How You Fit:

This is an individual contributor role within a product pod. You influence through your work — your code, your practices, your pairing, and the improvements that continue after you step away.

• With other Tech Leads: You may act as tech lead in a pod or work across pods alongside existing tech leads. When leading, you own technical direction. When partnering, you share practices, approaches, and architectural judgment.
• With Sr. Engineering Managers: You provide signal on team readiness, engineering gaps, and growth opportunities. They own the people conversations. You create the conditions for growth through pairing, modeling, and practical feedback from the work.
• With Product: You partner as a peer. You hold business context and technical context in the same conversation, helping define what is worth building and then building it.

Physical Requirements

• Prolonged periods sitting at a desk and working on a computer.
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