Senior Consultant, AI Engineer, Banking, AI Scaling & Transformation, AI & Data

Senior Consultant – AI & Data (Banking)

Deloitte’s AI & Data Financial Services team seeks a Senior Consultant to design and deliver AI solutions for banking clients. The role focuses on translating business vision into AI architecture, building prototypes, and producing production‑ready products within the Banking sector.

Location: London – hybrid working.

Responsibilities

• Supporting clients and Deloitte AI leads in translating vision into an AI architecture strategy and roadmap.
• Delivering rapid AI prototypes to prove a functional hypothesis.
• Building AI agents and products as part of a wider Data & AI transformation programme.
• Collaborating with fellow AI Engineers, Data Scientists, Business teams, MLOps/LLMOps engineers, and a broad spectrum of architects (Enterprise, Application, Data).
• Supporting technical decision‑making activities, including open‑source vs COTS product selection, AI deployment and serving patterns, integration patterns, and design decisions.
• Working with security and risk leaders to foresee and mitigate AI risks, ensuring ethical AI implementation and regulatory compliance.
• Assisting project teams with producing documentation for technical review boards and design authorities, ensuring compliance with data privacy, security and regulatory requirements in AI solution design and implementation.
• Building strong working relationships with clients’ technology teams.
• Contributing to project proposals, technology business case documents, and ROI measurement.
• Mentoring junior Deloitte colleagues through on‑the‑job training and support.

Qualifications

• Work experience delivering AI prototypes and large‑scale Data & AI implementations within the Banking sector.
• Strong collaboration skills with clients, actively listening to understand their business needs and challenges.
• Experience converting requirements and technical designs into value‑generating prototypes and solutions with architecture, engineering and test teams.
• Exposure to common software delivery methodologies and tooling (Agile/SaFe, Extreme Programming, Jira, Confluence, Linear, Monday).
• Demonstrated understanding of LLM fundamentals: prompt engineering, fine‑tuning, embedding models and RAG patterns.
• Knowledge of at least one vector database product (e.g., Pinecone, Chroma) and experience with an agent framework (e.g., LangChain, LangGraph, Agent Development Kit); exposure to MCP is preferred.
• Solid command of Python and SQL.
• Proven experience with modern data architectures and tooling, and a commitment to staying current with new techniques and technologies.

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