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$115,300 – $192,100
Listed on LSEG’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
A hands-on consulting role building agentic AI prototypes and leading innovation workshops for banking clients at a global financial infrastructure firm. Ideal for someone with both financial engineering experience and deep Python expertise across cloud AI platforms who thrives in fast-paced, experimental environments.
Our summary, not LSEG’s wording. The full posting is on their site.
Skills this role names
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What they ask for
Required
- 5+ years in financial engineering, quant analysis, or AI/ML engineering at a bank, trading firm, or financial market infrastructure
- Hands-on experience with agentic AI frameworks (LangChain, LangGraph, AutoGen, or Semantic Kernel)
- Strong Python with clean, documented, version-controlled code
- Azure AI Foundry: prompt flows, model deployment, evaluation, Azure OpenAI
- Microsoft Copilot Studio: custom copilot design and M365 deployment
- Databricks: Mosaic AI Agent Framework, Unity Catalog, MLflow, Model Serving
- Experience designing and delivering client-facing innovation workshops
- Excellent communication skills with C-suite and engineering audiences
- Azure AI Engineer Associate (AI-102) or Azure Data Scientist Associate (DP-100) certification
- Python certification (PCEP or equivalent minimum)
- Undergraduate degree in Computer Science, Financial Engineering, Data Science, Mathematics, or equivalent quantitative field
Nice to have
- Financial engineering background specifically from a bank (derivatives pricing, risk analytics, fixed income, quant research)
- Capital markets knowledge (equities, FX, rates, credit, commodities)
- Familiarity with LSEG Innovation Delivery Playbook and AI accelerator cataloguing methodology
- Experience with LSEG products (Workspace, DataScope, World-Check, Quantitative Analytics)
- Real-time market data and identifier mapping knowledge (RIC, ISIN, FIGI)
- Time-series databases experience
- Snowflake for governed analytical data access
- Design thinking certification or facilitation training
- CFA Level I or equivalent financial markets qualification
- Databricks Certified Machine Learning Associate or Associate Developer
- Certified Scrum Developer certification