Software Engineer

• Strong engineering fundamentals: clean code, healthy system design, logical thinking. Not knowing AI yet is not a dealbreaker if the fundamentals are there
• Must be a true engineer/coder. ML or AI backgrounds are welcome only if you genuinely build and ship code, not primarily train models as a data scientist or applied researcher
• 6+ years of professional software engineering experience
• Production experience with React or Next.js
• Proficiency in at least one of: Go, Python, or JavaScript (backend)
• Comfort navigating the full stack and pulling in what’s needed to ship
• A strong ownership mindset: takes problems from concept to production without hand-holding
• NY-based with the ability to work in-office (see schedule below)

A plus, not a requirement

• Background in recommendation, ranking/matching, or model-training systems (non-deterministic, optimization-driven work) - this mindset tends to transfer well to LLM-based product work
• Experience with AI tools, prompt engineering, or integrating LLMs into production applications
• Search infrastructure experience (Elasticsearch or similar)

• Base salary: $200,000 to $220,000
• Stock options
• Comprehensive medical, dental, and vision; 401(k); home office stipend; gym and commuter benefits

Our client, a profitable, founder-led career-services company serving millions of professionals, is hiring a Software Engineer to join as a Product Engineer on a lean, high-impact team building AI-powered features at scale.

This is not a backlog-ticket role. You’ll own product areas end to end, from concept through production, working directly with product design and engineering leadership to invent new AI/LLM-powered experiences. The company is EBITDA-positive, self-funded, and moving fast on AI integration after a recent growth inflection, so your work reaches real users immediately, not a backlog buried in a big-company queue.

What you’ll do

• Design and build AI-powered product features with real impact for millions of users, from concept through production
• Own product areas, services, or technical domains end to end; make structural technical decisions and clearly articulate trade-offs
• Build and maintain scalable backend services and user-facing applications; continuously improve performance, reliability, and developer experience
• Work as a genuine brainstorm partner with product design and engineering leadership to iterate on how AI/LLMs get implemented for specific use cases