AI Manager - SC Clearance Required
Posted 1 day ago by Jobserve
£719 Per day
Inside
Undetermined
London
Summary: The AI Manager role involves leading cross-functional engineering teams to design and deliver data-intensive platforms and AI-powered solutions. The position requires overseeing the entire data and AI lifecycle for Balance Sheet Management, ensuring alignment with business needs and performance standards. The manager will provide technical direction across data architecture and AI/ML capabilities while collaborating with stakeholders to prioritize backlogs and enforce engineering best practices. Strong knowledge of AI techniques and tools, as well as experience in regulated environments, is essential for success in this role.
Key Responsibilities:
- Lead cross-functional engineering teams to design, build, and deliver data-intensive platforms and AI-powered solutions.
- Oversee end-to-end delivery across the data and AI lifecycle for Balance Sheet Management.
- Act as the AIPX Delivery Manager, leading the design and build of robust data pipelines and high-quality derived data products.
- Provide strong technical direction across data architecture, cloud engineering, and AI/ML capabilities.
- Collaborate with product owners, data teams, and business stakeholders to prioritize backlogs and manage risks.
- Establish and enforce engineering best practices, including coding standards and DevOps/MLOps pipelines.
- Drive innovation by evaluating emerging data and AI technologies and leading proofs of concept.
Key Skills:
- Strong knowledge of AI techniques and experience applying AI in previous roles.
- Strong knowledge of AI tools to deliver faster idea to value.
- Strong knowledge of Gen AI models/LLMs and their application to use-cases.
- Experience in best practice delivery and production support in regulated organizations.
- Experience running fast-paced delivery teams aligned with business functions.
- Knowledge of Agentic Workflow/orchestration is an advantage.
- Knowledge of spec-driven development and new AI and engineering practices is an advantage.
Salary (Rate): £719/Day
City: London
Country: United Kingdom
Working Arrangements: undetermined
IR35 Status: inside IR35
Seniority Level: undetermined
Industry: IT
Detailed Description From Employer:
Lead cross functional engineering teams to design, build, and deliver data intensive platforms and AI powered solutions aligned to strategic business needs.
Oversee end to end delivery across the data and AI life cycle for Balance Sheet Management (BSM) -from data ingestion and modelling through to ML model development, deployment, and ongoing monitoring.
Act as the AIPX Delivery Manager by leading the design and build of robust data pipelines and the creation of high quality derived data products, ensuring alignment with AIPX architecture, performance standards, and business consumption needs.
Provide strong technical direction across data architecture, cloud engineering, and AI/ML capabilities to ensure scalable, secure, and well governed solutions.
Collaborate with product owners, data teams, and business stakeholders to prioritise backlogs, manage risks, and translate requirements into actionable technical plans.
Establish and enforce engineering best practices-including coding standards, DevOps/MLOps pipelines, testing frameworks, and documentation-to ensure high quality delivery.
Drive innovation by evaluating emerging data and AI technologies, leading proofs of concept, and embedding responsible AI principles across all project work.
Strong knowledge of big application development and working across tech teams of the bank
Knowledge required:
Strong knowledge of AI techniques, and approaches, showing experience of applying AI in previous roles
Strong knowledge of AI tools to deliver faster idea to value
Strong knowledge of Gen AI models/LLMs, and able to ascertain which to apply to particular use-cases
Experience in following best practice delivery and production support in a highly regulated organization
Experience of running fast paced delivery teams with close alignment to business functions
Knowledge of Agentic Workflow/orchestration an advantage
Knowledge of spec driven development and new AI and engineering practices to deliver an automated SDLC an advantage