Senior AI Engineer

Job Summary (List Format): Fraud Detection Agents - Design, build, and deploy fraud detection agents in C# using Microsoft Agent Framework. - Implement multi-agent workflows, tool calling, and human-in-the-loop approval processes. - Develop event-sequence detection to identify fraud patterns in account activities. - Build deterministic rules and risk-scoring logic for MVP, including case prioritization. - Transition detection logic from deterministic rules to generative AI methods. - Integrate anomaly reasoning, alert summarization, and agent-led investigation. - Ensure every alert includes explainability for fraud analysts (events, scores, evidence). AI Training Agents - Build AI training agents to generate and curate labeled fraud scenarios and synthetic datasets. - Develop feedback loops using analyst decisions to tune rules, prompts, and models. - Create evaluation frameworks to measure detection rates, false positives, and reasoning quality. Knowledge Graphs - Design, build, and maintain knowledge graphs in Neo4j/Stardog linking accounts, devices, transactions, etc. - Model graph ontologies and create queries (Cypher, SPARQL) to detect shared identifiers and fraud rings. - Integrate knowledge graph context into agent reasoning via retrieval and graph-based features. Engineering & Delivery - Collaborate with Solution Architect and Business Analyst to translate fraud scenarios and data requirements into solutions. - Build data pipelines to ingest authentication, recovery, account, and transaction events. - Apply software engineering best practices: version control, CI/CD, automated testing, monitoring, cost & latency management. - Ensure compliance with security, privacy, model risk, and audit requirements for financial crime systems. - Document design decisions and hand over solutions to support teams. Required Skills & Experience - 12+ years in software engineering; recent experience with generative AI applications and AI agents on cloud. - 1+ year hands-on with Microsoft Agent Framework (agent orchestration, tool calling, workflows). - Advanced skills in C# and .NET (async programming, dependency injection, API design). - Experience with Azure OpenAI/Microsoft Foundry and Azure cloud services. - Proficiency in knowledge graphs (Neo4j/Stardog, Cypher, SPARQL, ontology design). - Experience with event/time-series data and correlating events across sources. - Understanding of fraud and anomaly detection methodologies. - Experience designing evaluation/testing for LLM and agent outputs. - Ability to work with business/data/tech stakeholders and in regulated environments. Desirable Skills - Experience with graph data science (community detection, link prediction, graph embeddings). - Python skills for data science/model experimentation. - Familiarity with identity/document verification signals. - Knowledge of model risk management, responsible AI, and UK/EU AI regulations. - Relevant certifications (Microsoft Azure AI Engineer Associate, Neo4j Certified Professional).