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  • Full Stack AI Engineer - Sydney, New South Wales - Synechron

    Synechron
    Synechron Sydney, New South Wales

    2 months ago

    Description

    We are looking for a Full Stack AI Engineer will design, develop, and deploy scalable AI systems using the latest in LLMs, RAG, GenAI, and agentic multi-agent frameworks to deliver end-to-end AI-powered applications. The role requires strong skills in both back-end and front-end development, expertise in prompt engineering, and hands-on experience with vector databases, orchestration frameworks, and cloud infrastructure.

    Key Responsibilities

    • Architect, build, and deploy full-stack AI applications leveraging LLMs and GenAI models for enterprise use cases.
    • Implement and optimize retrieval-augmented generation (RAG) pipelines, including integration with vector databases (Pinecone, FAISS, Weaviate).
    • Develop multi-agent orchestration using frameworks such as LangChain, LangGraph,CrewAI, and AutoGen for autonomous task execution.
    • Design effective prompts and function-calling logic for context-aware AI agent workflows.
    • Collaborate with cross-functional teams (product, data, design) to translate requirements into production-grade AI systems.
    • Deploy, monitor, and maintain GenAI and agentic applications on cloud platforms (AWS,GCP, Azure), ensuring reliability and scalability.
    • Implement MLOps and CI/CD pipelines for continuous delivery, monitoring, and retraining of AI applications.

    Required Skills

    Strong proficiency in Python (data pipelines, AI integration), as well as back-end web frameworks (FastAPI, Flask, ).

    Experience with RAG architectures, vector search technologies, and multimodal AI design.

    This role is ideal for engineers passionate about building next-generation AI products that combine reasoning, retrieval, and autonomous agent workflows in real-world scenarios.

    Deep understanding of LLM orchestration, agentic systems, and generative AI concepts.

    Hands-on familiarity with prompt engineering, model evaluation, fine-tuning, and output optimization.

    Knowledge of containerization & orchestration (Docker, Kubernetes), cloud platforms, and Loops best practices.

    Preferred Skills

    • Experience integrating with front-end frameworks for AI-powered user experiences.
    • Proven track record of shipping reliable, maintainable AI products in production.
    • Familiarity with open-source AI/agentic tools and continuous evaluation frameworks (Agent Bench, RAGAS).

    Qualifications

    • Bachelor's or master's degree in computer science, Engineering, AI, Data Science, or related discipline (or equivalent experience).
    • 2+ years developing full-stack or AI/ML systems, with portfolio demonstrating LLM, GenAI, or agentic pipeline experience.

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