Transversal AI & Automation Enablement Engineer

Project overview

Job Title: Transversal AI & Automation Enablement Engineer Industry: Investment Banking Location: London (Hybrid) Contract: 6 months initial, with a view to extend | Inside IR35 Rate: Competitive

About the Role

Our client, a leading global investment bank, is growing its Data Operations (DataOps) function with a transversal role spanning four teams: ITAM Discovery, Data Visualisation, Project & Knowledge Management, and Data Protection. Each team has identified high-value AI/automation opportunities - this role exists to help deliver them, either by building solutions hands-on or by advising and equipping teams to build them. Candidates strong in either direction are equally welcome.

What You'll Be Doing

What We're Looking For

You don't need both skillsets below - strength in one is enough:

Desirable: cloud platforms (AWS/Azure/GCP); Docker/Kubernetes; MLOps/DataOps monitoring and testing

Personal Attributes: transversal mindset, proactive problem-solver or systems thinker, continuous learner, adaptable and pragmatic

Interested?

Whether your strength is hands-on delivery, technical advisory, or a mix of both, we'd love to hear from you.

Guidant, Carbon60, Lorien & SRG - The Vertage Group Portfolio are acting as an Employment Business in relation to this vacancy.

• Translate documented AI/automation use cases into technical designs, prototypes, or working solutions
• Build or advise on ETL/ELT pipelines preparing diverse datasets for AI consumption
• Implement or guide LLM-based solutions, including RAG systems and automation scripts
• Develop or lead the design of Proof of Concepts to validate AI ideas
• Act as a technical point of contact for AI/automation across DataOps, helping solutions be reused across teams
• Where relevant, mentor or support specialists within each team
• Experience in a data-centric or technical engineering role, with strong interest in AI/ML
• Strong Python and SQL
• Working knowledge of LLMs
• via APIs, RAG, or architectural design
• Solid data engineering fundamentals (data modelling, pipelines, structured/unstructured data)
• Strong communicator
• able to explain AI concepts to non-technical stakeholders, and/or advise others rather than only building solo
• Hands-on: building AI/ML pipelines or prototypes; vector databases; prompt engineering; orchestration tools (Airflow/Prefect); Git
• Advisory: designing AI/data architectures; Agentic AI principles (LangGraph, CrewAI, AutoGen); mentoring specialists without formal authority; AI governance (security, privacy, observability)

Project details

• Start: ASAP
• Duration: 6 Months
• Location: London, UK, GB