Overview
Deloitte's AI & Data Financial Services team focuses on developing AI solutions for the financial industry. The Manager role supports banking clients by delivering innovative solutions and driving continuous improvement.
Responsibilities
Supporting clients and Deloitte AI leads in translating vision into AI architecture strategy and roadmap.
Leading technical squads on Data & AI projects, AI prototyping, and experimentation sprints.
Collaborating with AI Engineers, Data Scientists, Business teams, MLOps/LLMOps engineers, and various architects.
Owning technical decision‑making activities, including open‑source vs COTS product choices, AI deployment patterns, integration patterns, and design decisions.
Working with security and risk leaders to mitigate AI risks, ensuring ethical AI implementation and regulatory compliance.
Preparing technical review boards and design authorities, ensuring compliance with data privacy, security and regulatory requirements.
Building strong client relationships.
Developing project proposals, technology business‑case documents, and estimating ROI of AI implementations.
Contributing to internal AI technical training pathways and mentoring junior colleagues.
Qualifications
Software/data engineering with proven experience in applied AI engineering, using Python and SQL. Experience in ML engineering and building API‑enabled backends such as FastAPI is preferred.
Experience with LLM fundamentals: prompt engineering, fine‑tuning, embedding models, RAG patterns and evaluation frameworks for agentic systems.
Comfortable with CI/CD tooling and ensuring good practices across the delivery team. Knowledge of MLOps/LLMOps is a plus.
Track record delivering agentic AI solutions, managing scope, and estimating build effort.
Proficient in software delivery methodologies: Agile/SaFe, Extreme Programming, Jira, Confluence, Linear, Monday.
Experience in the Financial Services industry, primarily the Banking sector.
Experience with at least one vector database (e.g., Pinecone), an agent framework (LangChain, LangGraph, Agent Development Kit), and MCP.
Strong understanding of modern data architectures and ability to identify technical and delivery risks.
Experience with at least one hyperscaler stack, preferably with certification (AWS, Azure, GCP, Databricks).
Excellent communication, stakeholder‑management, and collaboration skills; works effectively with multidisciplinary teams.
Problem‑solving mindset and ability to work independently.
Comfortable writing technical papers and AI business‑case documents.
#J-18808-Ljbffr
Deloitte's AI & Data Financial Services team focuses on developing AI solutions for the financial industry. The Manager role supports banking clients by delivering innovative solutions and driving continuous improvement.
Responsibilities
Supporting clients and Deloitte AI leads in translating vision into AI architecture strategy and roadmap.
Leading technical squads on Data & AI projects, AI prototyping, and experimentation sprints.
Collaborating with AI Engineers, Data Scientists, Business teams, MLOps/LLMOps engineers, and various architects.
Owning technical decision‑making activities, including open‑source vs COTS product choices, AI deployment patterns, integration patterns, and design decisions.
Working with security and risk leaders to mitigate AI risks, ensuring ethical AI implementation and regulatory compliance.
Preparing technical review boards and design authorities, ensuring compliance with data privacy, security and regulatory requirements.
Building strong client relationships.
Developing project proposals, technology business‑case documents, and estimating ROI of AI implementations.
Contributing to internal AI technical training pathways and mentoring junior colleagues.
Qualifications
Software/data engineering with proven experience in applied AI engineering, using Python and SQL. Experience in ML engineering and building API‑enabled backends such as FastAPI is preferred.
Experience with LLM fundamentals: prompt engineering, fine‑tuning, embedding models, RAG patterns and evaluation frameworks for agentic systems.
Comfortable with CI/CD tooling and ensuring good practices across the delivery team. Knowledge of MLOps/LLMOps is a plus.
Track record delivering agentic AI solutions, managing scope, and estimating build effort.
Proficient in software delivery methodologies: Agile/SaFe, Extreme Programming, Jira, Confluence, Linear, Monday.
Experience in the Financial Services industry, primarily the Banking sector.
Experience with at least one vector database (e.g., Pinecone), an agent framework (LangChain, LangGraph, Agent Development Kit), and MCP.
Strong understanding of modern data architectures and ability to identify technical and delivery risks.
Experience with at least one hyperscaler stack, preferably with certification (AWS, Azure, GCP, Databricks).
Excellent communication, stakeholder‑management, and collaboration skills; works effectively with multidisciplinary teams.
Problem‑solving mindset and ability to work independently.
Comfortable writing technical papers and AI business‑case documents.
#J-18808-Ljbffr
Contact Details:
Hm Revenue & Customs (Hmrc) Recruitment Team
