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Full stack Engineer AI systems

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Socket.dev
Full Time position
Listed on 2026-07-27
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Backend Developer, Full Stack Developer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 190000 - 250000 USD Yearly USD 190000.00 250000.00 YEAR
Job Description & How to Apply Below

OPEN TO US CITIZENS AND PERMANENT RESIDENTS

Role

We are looking for a Full Stack Engineer - AI Systems to build the product layer that turns these capabilities into usable, production-grade workflows. This includes designing how agents operate, fail, recover, and deliver consistent value to users.

Focus
  • Build end-to-end product features across frontend, backend, and AI integrations
  • Design agent workflows that handle planning, tool use, failure, and recovery across multiple steps.
  • Integrate LLMs, memory, and external tools into systems that behave reliably under real-world conditions
  • Design real-time AI interactions with streaming, partial results, and tight latency constraints
  • Improve system reliability, observability, and fallback mechanisms
  • Collaborate closely with ML, backend, and product teams to ship features end-to-end
  • Continuously iterate based on real usage and failure modes
Ideal Experiences
  • Strong experience in full stack engineering (frontend + backend)
  • Solid understanding of system design and API architecture
  • Experience working with LLMs, RAG systems, or AI-powered applications
  • Ability to handle ambiguity and make pragmatic engineering decisions
  • Strong ownership - able to take features from idea to production
  • Comfort working in fast-moving environments with evolving requirements
Outcomes
  • Own and ship AI-native product features that move beyond chat into persistent, goal-driven workflows
  • Design and deploy agent workflows that reliably complete multi-step tasks across tools and sessions
  • Reduce latency and improve responsiveness of AI interactions while maintaining output quality
  • Build robust fallback and recovery mechanisms for LLM and tool failures in production environments
  • Improve the success rate and reliability of AI-driven workflows through iteration, evaluation, and monitoring
  • Establish patterns and abstractions for integrating LLMs, memory, and external tools into scalable product systems
  • Contribute to a product experience where AI feels proactive, consistent, and dependable over time
Tech Stack
  • Next.js
  • Python
  • Node Js
  • Pytorch
  • OpenAI / Anthropic / open-source LLMs
  • SQL & noSQL
  • Kubernetes
  • Docker
How We Work

The best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product

Pay: $ - $ per year

Work Location:

Hybrid remote in San Francisco, CA 94102

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