Staff Software Engineer

About the Team

At AudioEye, we believe access to digital content is a fundamental right, not a privilege. Our mission is clear: eliminate every barrier to digital accessibility so that everyone, regardless of ability, can experience the web without limitations.

We are a team of passionate problem-solvers who are driven by purpose and impact. Every challenge we tackle moves us closer to a future where creating accessible experiences is the standard. If you’re looking for meaningful work where you can drive real change, influence how people with disabilities experience the internet, and be part of a mission that matters, AudioEye is the place for you.

About the Role

The Staff Engineer role helps to drive the technical direction of AudioEye’s platform and tackles complex challenges in digital accessibility. The position is responsible for designing and building large-scale, reliable systems that detect, remediate, and prevent accessibility issues across millions of websites, using AI and agentic development as a core part of how the work gets done. It blends architecture, hands-on development, and technical leadership to ensure systems are secure, scalable, and performant.

This role collaborates closely with the Product and Design teams to deliver systems that create measurable impact for customers and end users. The Staff Engineer mentors junior engineers on the team, helps shape the technical roadmap, and makes decisions that balance short-term delivery with long-term sustainability. It requires strong ownership, autonomy, and a focus on solving meaningful technical problems at scale.

How you’ll Contribute:

• Technically lead one or more engineering teams through needs assessment, system design, implementation, and operations automation
• Drive the technical roadmap, balancing short-term delivery with long-term sustainability
• Partner with Product, Design, and engineers to build systems that help customers respond quickly to risk, while keeping reliability, security, and data consistency high
• Build web-scale systems with strong grounding in service-oriented architecture, data modeling, performance, and end-to-end delivery
• Understand customer and end-user needs and turn them into measurable value
• Own problems across stacks, teams, and roles, with a bias for action
• Use AI coding assistants and agentic workflows daily to design, build, test, and operate software without lowering the quality bar. Delegate to agents, then review, verify, and take accountability for the output
• Evaluate new AI development tools and adopt those that measurably improve delivery
• Mentor and coach engineers on requirements, system design, problem-solving, and practical AI-assisted development, including prompting, context management, and knowing when not to trust the output
• Help define team standards for responsible AI use across code review, testing, security, and data handling
• Find opportunities to build AI capabilities into our products and internal tooling
• Build a culture of quality, high standards, and engineering excellence

Who you are:

• 10+ years of engineering experience with design, implementation, and operations of critical systems
• Demonstrated success working in cross-functional environments, advocate for tight collaboration between engineering, user experience, and product teams, and are comfortable making engineering and system-level decisions and tradeoffs
• Proficiency in modern JavaScript/TypeScript, including React and Node.js
• Experienced with relational, NoSQL, and document/object storage
• Proven record of solving deep problems in distributed systems and real-time data technologies
• Built and operated secure, compliant, scalable systems behind high-impact user experiences
• Led large projects across multiple teams and mentored both junior and senior engineers
• Collaborate tightly with Product and UX, and are comfortable making system-level tradeoffs
• Hands-on fluency with AI-assisted and agentic development, with concrete examples of how it changed how you build and ship
• Sound judgment on where AI helps and where it adds risk, and the discipline to validate generated code for correctness, security, and maintainability
• Have coached other engineers, including senior ones, to adopt AI-assisted workflows
• Thrive on autonomy and ownership, and adapt quickly as tools and practices change
• Model good engineering behavior, practices, and processes