Product Engineer

RealRecruit, LLC; United States; Remote; USD 120,000 - 170,000; Full time

Job summary

RealResponse is seeking a Product Engineer for a fully remote role in the United States. You will own problems end to end, from understanding customer needs to shipping fixes, while building and improving applications, and shaping products and internal tools.

The role emphasizes strong engineering practices, scalability, security, and cost-effectiveness, with a stack including Rails 8, Hotwire, Postgres, and AWS. Experience in evaluating models and designing multi-agent workflows is valued.

Qualifications

• Strong engineering practices and principles are valued.
• Ability to own problems end to end from understanding customer needs to shipping fixes.

Responsibilities

• Evaluate new models as they ship and pick the right one (speed vs capability).
• Design agents and multi-agent workflows with tool use, and judge when a simpler approach is better.
• Build retrieval that stays accurate as content changes (RAG, embeddings, search).
• Measure quality with evals and observability to prove changes.
• Keep AI features fast, reliable, and cost-efficient under production load.
• Handle AI security: prompt injection, data isolation, and sensitive data.

Skills

Problem solving

Engineering practices

System design

Tool judgment

Tools

Rails 8

Hotwire

Postgres

AWS

Job description

RealResponse | Product Engineer | REMOTE (US) | Full-time

We build software used across college athletics, professional sports, higher education, and other organizations, from reporting and compliance to live event operations. We're a team of We're looking for someone who solves problems across the board: building and improving our applications, shaping products, internal tools, fast prototypes, and the systems that keep quality and security high. You'd own problems end to end, from understanding what the customer actually needs to shipping the fix.

• Evaluate new models as they ship, and pick the right one for the job (fast and cheap vs. most capable)
• Design agents and multi-agent workflows with tool use, and know when a simpler approach is better
• Build retrieval that stays accurate as the underlying content changes (RAG, embeddings, search)
• Measure quality with evals and observability, so changes are proven rather than guessed
• Keep AI features fast, reliable, and cost-effective under real production load
• Handle AI security properly: prompt injection, data isolation between customers, and sensitive data

Stack today: Rails 8, Hotwire, Hotwire Native, Postgres, AWS. Rails experience helps but isn't required.

What matters more is a strong grasp of solid engineering practices and principles, and the judgment to use the right tools to solve the problem.