Design and develop a full-stack AI-native ecosystem, integrating LLMs and production-grade web applications. Ensure scalability, reliability, and user value. Collaborate with Product Managers to define the roadmap and coach non-technical users on AI capabilities.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
As a Full Stack AI Engineer, you will be responsible for the end-to-end evolution of our core platform; 482 Visa sponsorship is available for the right candidate. You aren't just building interfaces; you are architecting an AI-native ecosystem. You will bridge the gap between sophisticated LLM integrations (OpenAI, Claude) and production-grade web applications, ensuring that AI features are not just prototypes, but scalable, reliable tools that drive user value.
- Platform Evolution: Build and evolve a full-stack platform, ensuring architectural integrity and scalability.
- Backend & API Design: Design robust backend services and APIs using Python (FastAPI) to handle complex logic and third-party integrations.
- Frontend Excellence: Develop seamless frontend experiences using modern JS frameworks to make AI interactions intuitive.
- LLM Integration: Architect and implement advanced workflows with OpenAI and Claude, focusing on RAG pipelines and agentic reasoning.
- Cloud Infrastructure: Manage and deploy services within AWS, ensuring high availability and cost optimisation.
- Rapid Prototyping: Transition quickly from high-fidelity prototypes to stable, production-ready features.
- Collaborative Delivery: Pair closely with Product Managers to define the roadmap and coach non-technical users on AI capabilities.
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- End-to-End Proficiency: Extensive experience across the entire stack, equally comfortable with database schema design and frontend state management.
- Delivery Track Record: A history of shipping real-world products to production in fast-paced environments.
- Engineering Rigour: Solid understanding of API design patterns, microservices, and distributed systems.
- AWS Capabilities: Practical experience with AWS (Lambda, ECS, RDS, S3).
- AI Enthusiasm: A deep interest in the evolving AI landscape, specifically around LLM orchestration and vector databases.
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- Languages & Frameworks: Python (FastAPI), Modern JS (React/Next.js).
- AI & Intelligence: OpenAI, Claude, LangChain/LlamaIndex.
- Data Tier: PostgreSQL, Redis, Databricks.
- Infrastructure: AWS (Full Suite), Docker, Git.
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