Full Stack Engineer, AI Systems, Artificial Intelligence (AI) Required, Work From Home
- Role
- Fullstack
- Employment
- Full-time
Open to US only. Set where you work from to check your eligibility.
No BS summary
Full Stack Engineer for AI systems, fully remote, with strong frontend/backend experience and required AI experience. Needs LLM/RAG or AI-powered application experience plus system design and API architecture.
Core skills
Required skills
Full Stack Engineer, AI Systems, Artificial Intelligence (AI) Required, Work From Home 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. This position is 100% Remote. Full Stack Engineer Responsibilities: - 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. Full Stack Engineer 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.
Full Stack Engineer Qualifications: - Strong experience in Full Stack Engineering (Frontend and Backend). - Artificial Intelligence (AI) experience required. - 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. - Tech Stack: AI, Anthropic, API, Artificial Intelligence, Backend, Docker, Frontend, Kubernetes, Next.js, Node.js, NoSQL, OpenAI, Claude, Open Source, LLM, Python, Pytorch, RAG Systems, and SQL. Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc. Keywords: San Francisco CA Jobs, Full Stack Engineer, AI, Anthropic, API, Artificial Intelligence, Backend, Docker, Frontend, Kubernetes, Next.js, Node.js, NoSQL, OpenAI, Claude, Open Source, LLM, Python, Pytorch, RAG Systems, SQL, Programming, Programmer Analyst, Software Engineer, Software Developer, Work From Home, Remote, California Recruiters, IT Jobs, California Recruiting Looking to hire a Full Stack Engineer in San Francisco, CA or in other cities? Our IT recruiting agencies and staffing companies can help. We help companies that are looking to hire Full Stack Engineers for jobs in San Francisco, California and in other cities too. Please contact our IT recruiting agencies and IT staffing companies today!
What you'll do
- 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.
- 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.
What they require
- Strong experience in Full Stack Engineering (Frontend and Backend).
- Artificial Intelligence (AI) experience required.
- 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.
Benefits
- medical insurance
- Dental
- Vision
- Savings Plan Options
- PTO
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