AI Engineer - Banking Foundations

About the Role The Investigations team is on a mission to empower our financial crime investigators to work more efficiently and effectively by building tools that help them analyze complex cases, uncover suspicious activity, and protect our customers. We are making a strategic investment in AI to automate the core of the investigative process. We’re looking for a pioneering AI Engineer to join our team, serving as the critical productionizing partner for our Data Science (DS) and central AI teams. Your core mission is delivery, optimized for velocity and reliability: taking proven AI/ML models, LLM prototypes, and intelligent agents and integrating them directly into our product infrastructure. You will be obsessed with scalability, observability, and speed, ensuring our AI solutions move swiftly and reliably from a proof‑of‑concept to a production‑ready, highly monitored service that directly reduces investigation handling time. This role requires a unique T‑shaped skillset blending Data Engineering, Applied AI, and Backend expertise. What You’ll Do Drive Fast Time-to-Market (TTM) : Work collaboratively with the Data Science team to iterate quickly on prototypes, ensuring a seamless and rapid transition of validated models and LLM applications into the production environment. Productionize AI/LLM Prototypes : Act as the primary link between the DS/AI team\’s prototypes and the customer-facing product. You will refactor, deploy, and maintain robust, performant AI services (including LLM‑powered features and intelligent agents) in a high‑traffic production environment. Build Observability and Measurement Systems : Implement comprehensive observability solutions (metrics, tracing, logging) for all deployed AI features. Design and execute a framework for measuring output quality, A/B testing different models/prompts, and iterating on performance in real‑time. Architect for Reliability and Scale : Design and implement the technical architecture, data pipelines, and orchestration systems necessary to support AI services. Focus on building highly available, low‑latency APIs and ensuring proper monitoring, logging, and failure handling across the entire lifecycle. Design and Deploy Custom AI Services : Collaborate with the Platform Engineering team on leveraging foundational models (like those from AWS Bedrock/Anthropic) managed by them. Your focus will be on designing, building, and deploying the surrounding application logic and custom components, such as Multi‑step Control Program (MCP) servers, that interact with those foundational models. Apply Advanced AI Techniques : Directly implement and optimize advanced Applied AI techniques, such as Retrieval‑Augmented Generation (RAG), Multi‑step Control Programs (MCP), Agent-to-Agent (A2A) flows, and fine‑tuning methodologies. Contribute to Discovery : Leverage your deep understanding of system constraints, data availability, and production feasibility to proactively identify and recommend new AI use cases, working closely with Product and Data Science. What You’ll Bring Experience : Proven experience building, deploying, and maintaining machine learning or LLM‑based applications in a production environment. Hybrid Technical Skills : Backend Engineering : Proficiency in developing scalable, reliable backend services (mainly Python, Kotlin) with a focus on API design and microservices architecture. Applied AI Engineering