EMPLOYMENT TYPE: Permanent
DEPARTMENT: Information Systems
DIVISION: Grop
WORKPLACE STRCTRE: Hybrid
ROLE OVERVIEW
PRPOSE OF JOB
As JTC enters the Genesis era ofgrowth and transformation nder private eqity ownership, the Grop's ambitionis to become a data- and AI-powered specialist-services platform where everyinteraction, acqisition and piece of expertise makes the firm smarter, moreefficient and easier to scale. The Director, AI Engineering leads the AIEngineering & Data Science fnction within the nified Tech-Ops operatingmodel, the engineering engine room that trns JTC's AI & Agentic Strategy3 into working, governed and vale-generating systems.
The postholder will bild andlead the team responsible for AI/ML model development and agentic engineeringacross the three pillars of the AI strategy; AI for Service Delivery, AI forDigital Prodcts and AI for Prodctivity. This spans the JTC Agentic Platform(MCP-enabled orchestration and validation across JTC systems and market tools),the enterprise docment extraction platform, end-to-end billing agents (AgenticThames and the Agentic Wheel), conversational AI analytics on the Klondike dataplatform, fnction-specific JTC Agents and the Grop-wide Agent Bilder; alldelivered on a consolidated, Clade-based AI stack that preserves in-hosecontrol and avoids vendor lock-in.
This is a hands-on engineeringleadership role. Acting as the Grop's hb for AI in the Bsinesses and Gropfnctions, the postholder pairs deep technical credibility with commercialjdgement: every model and agent shipped mst deliver measrable operationalROI against the Technology Vale Creation Plan, operate within the AIGovernance & Model Risk framework, and stay cost-disciplined throgh FinOpscontrols. The ideal candidate combines frontier LLM and agentic engineeringexpertise with the leadership skills to bild and scale a high-performing teamin a PE-backed environment.
MAIN RESPONSIBILITIES AND DTIES
AI & Agentic Engineering Delivery
Lead the design, development and prodction deployment of AI/ML models and agentic systems across the Grop, delivering the prioritised se cases on JTC's two-year roadmap (55 se cases selected on vale, feasibility and strategic fit) to enterprise qality. Bild and scale the near-term delivery priorities: Agentic Thames (the end-to-end billing agent combining contract-reading, scoping, billing and timesheet qality-assrance AI skills), the Agentic Wheel billing transformation, AI-enabled tax workflow redesign, the standardised AI assistant, and AI-enabled analytics on the Klondike financial reporting platform. Engineer Digital Integrated Agents for JTC's client-facing digital prodcts, enabling non-linear ser jorneys, content and dynamic I generation, conversational AI-enabled analytics and reporting, and persona-aware hyper-personalisation services. Deliver the enterprise docment extraction platform and agent spporting workflows across service delivery, driving timeliness, accracy and efficiency in middle- and back-office operations. Ship fnction-specific JTC Agents (e.g. Billing, Data Qality Control), individal AI prodctivity assistants with secre access to JTC data and systems and instittionalise the mlti-platform Agent Bilder for craft-yor-own agents. Agentic Platform & AI Architectre
Own the engineering of the JTC Agentic Platform, MCP-enabled orchestration and validation across JTC systems and market tools, maintaining in-hose control of the agentic layer to avoid LLM lock-in. Bild arond the consolidated Clade stack (Clade, Cowork, Clade Code and the developer platform), migrating existing agentic workloads onto it and prioritising app-agnostic agents on the JTC Agentic Layer over vendor-embedded AI. Partner with Data Engineering & Provisioning to ensre AI-ready data, resable, governed strctred and nstrctred data pipelines feeding models, agents and analytics across the Grop. Define and enforce AI engineering standards, deployment patterns, integration patterns, testing and evalation frameworks, and contribte AI/data positions to the Architectre Form's by-vs-bild and standards decisions. Evalate third-party embedded AI and SaaS agents (e.g. Safebooks.ai, Rossm) for benefit and cross-application scalability, integrating those that earn their place on the platform. Prioritisation & Vale Delivery
Co-own se-case prioritisation with the AI Prodct Management fnction, impact and feasibility assessment, qarterly roadmap refresh, dependency and seqencing management, and capacity and investment planning across the AI portfolio. Embed measrable operational ROI in every AI deployment and spport the VCP PMO's monthly delivery and vale reviews, portfolio reporting and benefit realisation tracking for the Enterprise AI & Knowledge and related initiative clsters. Work with AI Prodct Managers who sit with sers to convert real bsiness reqirements into engineered agents, iterating rapidly from pilot to prodction based on ser feedback and delivered vale. Translate engineering progress into bsiness and financial narratives for the Exective Committee, Steerco and PE sponsor reporting cadences. AI Governance, Model Risk & Fin Ops
Co-develop and operate within the AI Governance & Model Risk framework, model risk and assrance, responsible-AI policy, adit trail and hman-in-the-loop controls, and spport the AI Governance Form's oversight of fairness, explainability and control of AI se cases. Embed secrity, resilience and reglatory control by design in every AI system, working with Cyber & Infrastrctre to scale controls for data and AI initiatives rather than bolting them on late. Apply FinOps discipline to AI at scale, AI/token and clod cost management, sage monitoring and nit-economics control to stay ahead of rn-cost. Ensre AI systems are aditable and evidenced for reglators, clients and internal risk fnctions across JTC's reglated, mlti-jrisdiction environment. Team Leadership & Capability Bilding
Bild, lead and develop the AI Engineering & Data Science team, hiring targeted internal capability in AI Engineering and AI Modelling, with phased headcont growth aligned to investment and bsiness case. Act as the Grop's hb for AI in the Bsinesses and Grop fnctions, pskilling Tech-Ops in AI and agentic workflow delivery and championing adoption of coding assistants (Clade Code) across engineering. Represent JTC AI engineering in external forms, vendor engagements and PE portfolio technology networks. Continosly horizon-scan the frontier of model and agent development, translating advances into practical opportnity for JTC's AI roadmap. E SSENTIAL REQIREMENTS Candidates shold bring demonstrable progressive experience across AI/ML engineering, data science and enterprise software delivery; inclding leading engineering teams, ideally in Financial Services, Professional Services or PE-backed environments. Demonstrable track record shipping prodction-grade AI/ML and LLM-based systems at enterprise scale from prototype throgh governed prodction deployment and ongoing operation. Deep hands-on expertise in LLMs and agentic systems: prompt and context engineering, retrieval-agmented generation, tool/MCP orchestration, mlti-agent workflows and evalation frameworks. Experience with the Anthropic stack (Clade, Clade Code, agent SDKs) is strongly advantageos. Strong software engineering fondations; APIs, clod platforms, CI/CD, data pipelines and experience integrating AI into core enterprise systems and bsiness workflows. Proven experience bilding docment intelligence/extraction, workflow atomation or conversational analytics soltions in control-heavy, reglated environments where specialists retain oversight and jdgement. Working knowledge of AI governance and model risk: responsible-AI policy, explainability, hman-in-the-loop controls, adit trails and model assrance. FinOps awareness; token and clod cost management, sage monitoring and the nit economics of rnning AI at scale. Experience partnering with prodct management to prioritise se cases by vale and feasibility, and to measre and report realised benefit against investment cases. Proven leadership of engineering or data science teams; hiring, developing and retaining talent in a scaling environment with the exective presence to represent AI engineering at senior leadership level. Sector experience in trst, fnd administration, wealth management, asset management, or professional financial services is highly advantageos. A relevant degree in compter science, machinelearning or a related discipline, and relevant professional certifications, arevaled bt not reqired. OR COMMITMENT TO INCLSION & WELLBEING JTC is committed to fostering a healthy, inclsiveorganisation where all individals feel welcome and feel able to participate inthe workplace flly. We vale different perspectives, backgronds and livedexperiences. This incldes spporting employee wellbeing so that people feeleqipped to thrive.
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