Job Description

About the role:

Dice is the career marketplace for technologists, which means the product you’d build here is the one you’d use to find your next role. We’re rebuilding it end to end: how a job seeker finds their next role, and how recruiters and employers find and connect with them.

As a Staff Software Engineer, you’ll set the technical direction for that platform, take on our hardest and most ambiguous problems, from search relevance and classification to performance at scale and platform integrations, and make the engineers around you better, on a team that treats AI as a core part of how we build, not a side experiment. You’ll partner closely with Product, Design, Data, and engineering leadership to turn our biggest candidate and recruiter problems into shipped outcomes.

This is a hands-on role. You’ll be in the code, building and shipping alongside the engineering team, and your influence is earned through the work.

About the team:

We believe an exceptional candidate and recruiter experience is what makes our platform win, and we’re building the next generation of it across a modern full-stack environment. You’d join a small group of Staff and Principal engineers setting technical direction across our three feature teams. We value engineers who are curious, collaborative, and want their work to matter for the people using it.

AI-native:

• We start with AI: the engineers who thrive here keep asking “why are we still doing this by hand?” and then automate it, with real autonomy and leadership backing.
• We hire for judgment first: thoughtful design, holistic product thinking, sound principles, and strong fundamentals are what make great engineers, and AI multiplies exactly those.
• We use AI agents across the lifecycle: writing and reviewing code, generating tests, triaging dependencies, and building internal tooling.

In the short term, you will:

• Get the lay of the land: dig into our applications, services, and architecture and the teams they span, and pick the highest-leverage problems to put your judgment on.
• Own real problems early: take on hard problems from day one, shape design and reviews across teams, and build the credibility to steer direction beyond your own team.
• Plug into the network: work shoulder to shoulder with engineers, Staff peers, PMs, designers, and engineering leadership, and start unblocking work across teams.

In the long term, you will:

• Set technical direction: own architecture and technical standards that span multiple teams and quarters. Evolve our systems, reduce systemic tech debt, and raise the engineering bar, including how we apply AI across the workflow.
• Multiply the team through leadership: mentor and sponsor engineers at every level, model the standard others follow, and create leverage by making the engineers and systems around you better, not only through your own output.
• Drive the hardest problems to done: carry our most ambiguous, high-impact, cross-team initiatives from unclear problem to shipped outcome, and influence the roadmap by advocating for the right technical investments for the business and our users.

What you’ll need (must-haves):

• Depth in a modern cloud stack: you’ve built and operated production-grade, business-critical systems end to end, across backend, data, and cloud. Ours is Node.js/TypeScript on AWS with PostgreSQL and React/Next.js.
• Product and UX first: you start from the user and the product, and let that drive how you build.
• Data as the foundation: you understand that data is what the whole product is built on, you reason about how it’s modeled and how it flows across the system, and you have the data-modeling and schema fundamentals to back it up.
• AI-native ways of working: you already use AI coding agents as a core part of how you build, going well beyond a chat assistant, and you help others adopt AI safely and effectively.
• Staff-level scope and judgment in ambiguity: you’ve owned high-impact problems that span multiple teams and quarters, weighing trade-offs across systems and time, defining the path when the problem isn’t yet scoped, and carrying it to done.
• Hands-on execution: you’ve stayed close to the code, building and shipping alongside your team, and you lead by doing.
• Technical leadership through others: you’ve set architectural direction and grown the engineers around you through mentorship and sponsorship.
• Influence through communication: you’ve built consensus across teams by writing and explaining clearly, earning buy-in rather than relying on mandate.

Bonus points (preferred, not required):

• You’ve guided technical strategy and led initiatives that span multiple teams or domains.
• You’ve applied LLM-based tooling to practical data problems like enriching and classifying content.
• You’ve worked with event-driven and microservice architectures.
• You’ve modernized or migrated legacy systems while balancing technical debt and business needs.
• You’ve tuned performance and optimized cost in cloud-native environments.
• You’ve worked on highly available, consumer-facing SaaS or marketplace applications.
• You’ve worked in Python and/or Java, across OOP and functional paradigms.

NOTE:

This job description is not intended to be an all-inclusive list of the duties and responsibilities of the job described, nor are they intended to be such a listing of the skills and abilities required to do the job. Rather, they are intended only to describe the general nature of the job as of the date this job description was prepared. Management reserves the right to modify this job in order to meet business needs.

All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.