Senior Product Engineer, Cresta Labs

Cresta Cresta · Vertical AI · United States · Remote · Engineering

Senior Product Engineer at Cresta Labs, focusing on building and shipping AI-native product experiences. The role involves working across the full product development loop, from identifying user needs to productionizing AI agents and improving development, testing, evaluation, monitoring, and optimization workflows. Requires strong full-stack and applied ML skills, with experience in LLMs and AI agents.

What you'd actually do

  1. Build zero-to-one AI product experiences from early concept through prototype, validation, and productionization.
  2. Work with users, product managers, designers, researchers, engineers, and customer-facing teams to identify high-impact opportunities.
  3. Translate ambiguous customer needs and product ideas into clear workflows, interfaces, and technical designs.
  4. Build and improve AI agent development, testing, evaluation, monitoring, and optimization workflows.
  5. Use product data, user feedback, and evaluation results to understand what is working and what needs to improve.

Skills

Required

  • 5+ years as a software/ML engineer on user-facing systems with strong full-stack engineering skills.
  • Experience building and shipping products or major features with significant end-to-end ownership.
  • Hands-on experience with LLMs, AI agents, AI workflows or applied ML products.
  • Strong product judgment and the ability to simplify complex technical ideas into intuitive user experiences.
  • Comfort working in ambiguous problem spaces where the right answer is not yet obvious.
  • Ability to move quickly from idea to prototype while maintaining strong engineering rigor.
  • Strong communication skills, especially when explaining technical concepts to cross-functional audiences.

Nice to have

  • Experience designing and building evaluation and testing frameworks for machine learning systems
  • A practical approach to validation, including user research, instrumentation, metrics, and evaluation.
  • Previous experience in a startup or fast-paced product environment

What the JD emphasized

  • significant end-to-end ownership
  • Hands-on experience with LLMs, AI agents, AI workflows or applied ML products
  • Comfort working in ambiguous problem spaces where the right answer is not yet obvious.
  • Ability to move quickly from idea to prototype while maintaining strong engineering rigor.

Other signals

  • building next generation of AI-native product experiences
  • exploring and building
  • full product development loop
  • hands-on builder role
  • move quickly from idea to prototype