AI Product & Research Engineer

GalaxyNew York, NY
3h

About The Position

We are seeking a AI Product & Research Engineer to help design, prototype, and scale enterprise-grade AI products. This role combines deep technical AI expertise with strong product intuition and hands-on experience leveraging modern AI development tools and coding agents. You will work closely with leadership, engineering, and research teams to translate ambitious AI concepts into deployable, secure, and scalable production systems.

Requirements

  • 5 - 8+ years of experience across AI/ML engineering, applied research, or AI product development.
  • Demonstrated experience building and shipping enterprise-grade AI products.
  • Deep familiarity with modern AI stacks (LLMs, RAG systems, fine-tuning, embeddings, orchestration frameworks).
  • Hands-on experience using AI coding agents and AI-assisted development tools in production workflows.
  • Strong product instincts: ability to balance technical feasibility, business value, and user experience.
  • Proficiency in Python and modern AI frameworks.

Nice To Haves

  • Experience deploying AI systems in regulated or security-sensitive environments.
  • Familiarity with distributed systems and cloud-native architectures.
  • Background working at leading AI labs, big tech, or high-performance startups.
  • Experience designing internal AI platforms used by multiple teams

Responsibilities

  • Translate business and research objectives into scalable AI product architectures.
  • Rapidly prototype AI-driven applications using modern AI coding agents and developer copilots.
  • Design and implement enterprise-grade AI systems across model development, evaluation, and deployment.
  • Lead applied research efforts across LLMs, agentic systems, retrieval architectures, and applied ML.
  • Establish evaluation frameworks to measure model quality, safety, robustness, and business impact.
  • Architect production-ready AI applications with strong observability, monitoring, and iteration loops.
  • Advise on AI tooling, vendor selection, infrastructure alignment, and technical roadmap decisions.
  • Mentor internal engineers on modern AI development workflows and best practices.
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