ai full stack engineer.

We are looking for a systems-thinking Senior Full-Stack AI Engineer to bridge the gap between advanced AI orchestrations and seamless user experiences. In this role, you will design and build production-grade multi-agent systems and stateful workflows while crafting the responsive, intuitive frontends needed to interact with them.

You won’t just be plugging in basic LLM wrappers. You will be architecting complex, deterministic AI engines, exposing them via secure Python APIs, and building modern UIs that handle real-time, asynchronous AI events. If you are a product-minded full-stack developer who holds a Google Professional Cloud Architect certification, we want you on our team.

What You’ll Do

• Build Multi-Agent AI Workflows: Design and deploy stateful AI workflows and multi-agent systems using Google ADK, LangChain, and LangGraph.
• Develop Secure Full-Stack Architectures: Write secure Python APIs optimized for agent tool calling and connect them to responsive, modern frontend applications.
• Master State & Memory Management: Implement system instructions, persistent memory, and context window management to handle complex user-agent interactions.
• Enforce Structured Outputs: Keep LLM outputs predictable using rigorous JSON schemas and Pydantic validation, translating them smoothly to the frontend.
• Implement Guardrails & Real-Time UX: Build resilience using backend circuit breakers and fallback logic, paired with graceful UI handling for loading states and streaming responses.
• Drive Observability & Evals: Establish “evals-as-code” by tracing agent reasoning paths and automating prompt testing pipelines.

• Full-Stack Proficiency: Strong background in backend Python (APIs, microservices, system design) paired with production experience in modern frontend frameworks (e.g., React, Next.js, or Vue).
• LLM Orchestration: Hands-on experience building production workflows with LLM APIs (Gemini, OpenAI, Claude) and orchestration frameworks (LangGraph/LangChain).
• GCP Expert (Required): Deep understanding of Google Cloud services and infrastructure. You must hold an active Google Professional Cloud Architect certification.
• Cloud Native & Real-Time Web: Comfortable with containers (Docker), CI/CD pipelines, and real-time frontend communication (WebSockets, Server-Sent Events for streaming AI responses).
• A Testing Mindset: Experience writing unit and integration tests for both frontend interfaces and probabilistic, non-deterministic AI systems.
• Systems & Product Thinker: Ability to conceptualize complex backend decision trees and translate them into intuitive, user-friendly UI/UX.