Full Stack Engineer AI Systems

European Recruitment BV; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

European Recruitment BV is seeking a Full Stack Engineer specializing in AI Systems to build the product layer that translates AI capabilities into production-ready workflows. You will design how agents operate, fail, recover, and deliver consistent value to users in a fast-moving environment.

Ideal candidates have strong full stack experience, system design expertise, and familiarity with LLMs and RAG systems to ship features end-to-end with ownership.

Qualifications

• 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.

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.

Skills

Full stack engineering

System design

LLMs / RAG

Ambiguity handling

Ownership

Fast-moving environments

Tools

Next.js

Python

Node.js

PyTorch

OpenAI / Anthropic

SQL

NoSQL

Kubernetes

Docker

Job description

Full Stack Engineer AI Systems

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

• NodeJs

• Pytorch

• OpenAI / Anthropic / open-source LLMs

• SQL & noSQL

• Kubernetes

• Docker