Senior AI Engineer

Senior AI Engineer

Join our AI Practice, and support key long-term programs of work!

FinXL Professional Services is a leading IT consultancy that partners with clients to bridge the gap between business needs and technology capabilities. Since 2003, we've been delivering high-value ICT services across government, finance, telecommunications, and enterprise sectors.

FinXL is seeking a Senior AI Engineer to join our consulting team and be deployed with a leading banking client on a 6-12 months contract in Sydney CBD. This position combines deep hands-on development with cutting-edge AI solution architecture, serving as a technical spearhead for next-generation intelligence initiatives. You will design, build, and deploy enterprise-grade Agentic AI and Graph-RAG systems, anchoring critical regulatory and governance workflows while driving robust, traceable machine learning capabilities into production. Support key long-term programs of work! Neo4j, Graph-RAG and Agentic AI!

Responsibilities

• Architect resilient, scalable, and secure end-to-end solutions for generative and agentic AI systems.
• Construct and fine-tune enterprise knowledge graphs to facilitate hybrid vector and graph traversal retrieval.
• Build autonomous, multi-step agent frameworks equipped with tool-calling capabilities and deterministic verification.
• Deliver clean, maintainable production-grade code alongside robust continuous integration and automated deployment pipelines.
• Establish comprehensive evaluation suites, guardrails, and mitigations against model hallucination and bias.
• Collaborate closely with risk specialists, data governance teams, and enterprise architects to ensure audit compliance.
• Drive the integration of structured semantic data models with downstream large language model workflows.

Key Skills & Experience

• Extensive background in software and machine learning engineering with a history of deploying LLM systems to production.
• Advanced expertise in graph database modeling, Cypher optimization, and knowledge graph integration using Neo4j.
• Strong practical command of Graph-RAG architectures unifying unstructured data retrieval with structural semantics.
• Proven capability in developing autonomous or stateful agent frameworks using ecosystems such as LangGraph or AutoGen.
• High proficiency in Python programming, modern LLM orchestration libraries, and secure API development.
• Working familiarity with cloud deployments (AWS), containerization, and enterprise MLOps lifecycle practices.
• Exposure to financial services, prudential frameworks (e.g., APRA, Basel), or regulatory risk governance is highly regarded.

Engagement Details

• 6-12 months contract with a leading banking client.
• Hybrid working model with 3 days/week in the office in Sydney CBD.