Senior Innovation Consultant (Agentic AI Consulting)

About The Role Join LSEG’s Innovation Team (Customer Consulting Group) as a Senior Innovation Consultant (Agentic AI Consulting) — a role for someone who can lead an AI ideation workshop in the morning and ship a working multi-agent prototype by end of day.

We need a rare profile: genuine financial engineering experience from a bank or trading firm, paired with hands-on Python engineering across Azure AI Foundry, Microsoft Copilot Studio, and Databricks.

At a Glance — What You’ll Own

• Lead Agentic AI Innovation — End-to-end ideation and architecture of cloud-native agentic AI solutions for global banking and financial services clients.
• Prototype & Engineer Fast — Build POCs and demos in Python using Azure AI Foundry, Copilot Studio, and Databricks Mosaic AI — clean, documented, version-controlled code.
• Run Client Workshops — Plan and deliver innovation workshops using design thinking, from problem framing to co-created prototype roadmap.
• Drive Pre-Sales Growth — Contribute SOW inputs, LOE estimates, architecture decks, and live demos to support commercial pipeline across capital markets.
• Must Have — Financial engineering background from a bank or trading firm. Hands-on Python. Certified Azure AI / Databricks. Fail-fast mindset.

What You’ll Do Solution Ideation & Architecture

• Lead client ideation sessions — define opportunity areas, shape agentic AI use cases, and translate them into reference architectures and prototype tech stacks.
• Design multi-agent orchestration patterns: agent routing, tool calling, memory management, and guardrails suited to financial services environments.
• Apply design thinking to frame user journeys and desired business outcomes from workshop to first prototype.

Rapid Prototyping & Engineering

• Build agentic AI prototypes in Python — multi-agent pipelines, RAG systems, tool-use workflows — using LangChain, LangGraph, AutoGen, or Semantic Kernel.
• Azure AI Foundry: configure model deployments, prompt flows, evaluation pipelines, and content safety filters.
• Microsoft Copilot Studio: design custom copilots, configure knowledge sources and Power Platform connectors, publish to Microsoft 365 / Teams.
• Databricks: build with Mosaic AI Agent Framework, Unity Catalog, MLflow, and Model Serving for governed, low-latency agentic workloads.
• Integrate LSEG data — RDP APIs, MCP Connectors, Real-Time Optimized feeds — into AI-driven financial workflows.
• Deliver reusable accelerators, notebooks, and demo assets. Scope is prototype-level only — not production or BAU.

Client Workshops & Delivery

• Plan, facilitate, and own end-to-end delivery of innovation workshops — from problem framing to prototype roadmap.
• Work alongside cloud engineers, architects, consultants, and project managers in a fast-paced, agile sprint rhythm.

Pre-Sales & Commercial Support

• Contribute SOW inputs, LOE estimates, and solution narratives to commercial proposals.
• Build and present live demos and prototype showcases that bring LSEG’s AI capabilities to life for prospective clients.

Skills & Experience Required (Must Have)

• 5+ years in financial engineering, quant analysis, or AI/ML engineering at a bank, trading firm, or financial market infrastructure.
• Hands-on agentic AI: LangChain, LangGraph, AutoGen, or Semantic Kernel.
• Strong Python — clean, documented, version-controlled; async patterns, API wrappers, Jupyter Notebooks.
• Azure AI Foundry: prompt flows, model deployment, evaluation, Azure OpenAI (GPT-4o, o1).
• Microsoft Copilot Studio: custom copilot build, topic authoring, connector integration, M365 deployment.
• Databricks: Mosaic AI Agent Framework, Unity Catalog, MLflow, Model Serving.
• Experience designing and delivering client-facing innovation workshops.
• Excellent communication — comfortable with C-suite and engineering audiences.

Desired (Nice to Have)

• Financial engineering from a bank is a clear winner: derivatives pricing, risk analytics, fixed income, or quant research.
• Capital markets knowledge: equities, FX, rates, credit, or commodities.
• Familiarity with the LSEG Innovation Delivery Playbook (LIDP) and the firm’s internal AI accelerator cataloguing methodology — experience aligning prototype outputs to LIDP sprint frameworks is highly valued.
• LSEG product experience: Workspace, DataScope, World-Check, or Quantitative Analytics.
• Real-time market data, identifier mapping (RIC, ISIN, FIGI), time-series…