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AI Engineer, Agent Systems

San Francisco

SpringCube

Full-time - Senior Engineer

IT Cloud Computing, Software & SaaS

Posted 3 weeks ago

Disclosed upon interview

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Job Description

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.

Company Overview

A technology company focused on developing ambitious artificial intelligence products is seeking an AI Engineer, Agent Systems to join its engineering team. The organization is building AI-powered products that rely on frontier model APIs and requires engineers who can develop reliable, production-ready systems around large language models.

The role focuses on the model-facing layer of AI products, including retrieval and RAG pipelines, agent planning and orchestration, multi-agent frameworks, and context engineering. The successful candidate will have hands-on experience shipping LLM-powered features to real users and will approach quality, cost, and latency as core engineering constraints.

About the Role

The AI Engineer will design and build product features on top of frontier model APIs while owning model-layer systems from initial design through production. The role requires deep practical experience with LLM APIs and the ability to develop reliable AI systems that perform effectively in real-world production environments.

Candidates with backgrounds as GenAI Engineers, LLM Engineers, RAG Engineers, or Algorithm Engineers may find their experience particularly relevant to this opportunity.

Compensation

  • Competitive salary
  • Meaningful equity

Key Responsibilities

  • Design and build product features using frontier model APIs.
  • Build, optimize, and maintain end-to-end retrieval and RAG pipelines.
  • Design agent planning, tool-use, and multi-agent orchestration systems.
  • Develop and maintain disciplined, tested approaches to prompt and context engineering.
  • Integrate evaluation systems into the development lifecycle to measure and improve AI quality.
  • Optimize AI features for cost, quality, and latency in production environments.
  • Collaborate with product and engineering teams to deliver reliable products quickly.
  • Own model-layer systems from architecture and implementation through production deployment.
  • Develop production features that provide reliable and high-quality experiences for end users.

Required Qualifications

  • Proven experience shipping LLM-powered features to production.
  • Strong software engineering foundation.
  • Working knowledge of retrieval, RAG, and AI agent patterns.
  • Fluency with modern model APIs and AI development tooling.
  • Strong judgment regarding quality, cost, and latency trade-offs.
  • Clear written and verbal communication skills.
  • Ability to operate effectively in a fast-moving environment.
  • Demonstrated ability to build high-quality technical systems and products.
  • Deep, hands-on experience developing production features on top of LLM APIs.

Preferred Qualifications

  • Experience with multi-agent frameworks or agent orchestration systems.
  • Experience building or working with evaluation harnesses.
  • Experience with TypeScript, Python, Node.js, Postgres, or similar technologies.
  • Experience with fine-tuning or model adaptation.
  • Experience developing production-grade AI applications.
  • Familiarity with advanced context engineering and model optimization techniques.

Disclaimer

SpringCube curates tech job listings from various company websites to support tech professionals globally.

  1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
  2. No Client Relationship: This company is not a client of SpringCube unless stated.
  3. To Apply: Click the Apply button to be redirected to the hiring company’s application page for this job.
  4. No Liability: SpringCube is not liable for inaccuracies.
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