AI Engineer

IC Markets Global is one of the most renowned Forex CFD provider, offering trading solutions for active day traders and scalpers as well as traders that are new to the forex market. IC Markets Global offers its clients cutting edge trading platforms, low latency connectivity and superior liquidity.IC Markets Global is revolutionizing online forex trading. Traders are now able to gain access to pricing previously only available to investment banks and high net worth individuals.Our management team have significant experience in the Forex, CFD and Equity markets in Asia, Europe and North America. It is this experience that has enabled us to select the best possible technology solutions and hand pick some of the best pricing providers available in the market.About the RoleWe are seeking a skilled and experienced AI Engineer to join our team. In this role, you will be responsible for designing, developing, and deploying production-grade AI systems and intelligent agent pipelines. You will work at the intersection of software engineering and applied artificial intelligence, building scalable, reliable, and high-performance solutions.Key ResponsibilitiesDesign and deploy production-ready Python services powering AI capabilities, leveraging FastAPI for robust API development.Architect and fine-tune end-to-end agent workflows supporting chat, search, and retrieval use cases.Develop intelligent agents using LangChain, LangGraph, and LangSmith, encompassing prompt engineering, integration, and comprehensive testing.Integrate and optimize vector databases (Qdrant, Milvus, etc.) for embeddings management, high-speed lookups, and hybrid search functionality.Continuously evaluate and monitor agent performance to ensure reliability, accuracy, and consistency in production environments.Optimize agent systems for reduced latency, cost efficiency, and horizontal scalability.Required Qualifications3+ years of total software engineering experience, with a strong foundation in backend development using Python.1–2+ years of hands-on experience deploying and maintaining ML/AI systems in production environments (beyond research or proof-of-concept stages).Demonstrated proficiency in Python and software engineering best practices, with a focus on clean, maintainable, and production-quality code.Solid experience with NLP, Retrieval-Augmented Generation (RAG), embeddings, and vector databases such as Qdrant and Milvus.Deep expertise in LangChain and/or LlamaIndex for building agentic AI systems.Strong experience with Langsmith, understanding Evaluation Benchmarking and TracingProven experience in prompt engineering and systematic agent testing methodologies.Strong understanding of LLM inference pipelines, both on local infrastructure and cloud platforms.Proficiency with Docker and cloud platforms (AWS, GCP, or Azure).Demonstrated ability to design clean, well-documented APIs and integrate seamlessly with existing backend systems using a microservices architecture.