Senior AI Engineer Manager/Associate Director Capital Markets in Manchester

Senior AI Engineer Manager/Associate Director – Capital Markets

Location: Manchester | Working pattern: Hybrid | Salary: Compensation aligned to experience and seniority

This role requires senior AI engineering professionals to design, build, and deliver advanced AI solutions within financial services and capital markets environments. The successful candidate will shape AI strategy, lead teams, and deliver enterprise AI solutions that address complex operational, technical, and regulatory challenges at scale.

Responsibilities

• Build and deploy AI prototypes, products, and production‑ready solutions.
• Design and implement end‑to‑end AI solutions that integrate with enterprise systems.
• Work with large language models, prompt engineering, RAG patterns, embeddings, and fine‑tuning.
• Develop AI agents and agentic workflows using modern frameworks.
• Use vector databases, APIs, and modern data platforms.
• Support AI deployment, serving patterns, evaluation frameworks, and integration design.
• Use Python and SQL to build robust, scalable AI and data solutions.
• Work with cloud platforms such as AWS, Azure, GCP, or Databricks.
• Support MLOps, LLMOps, CI/CD, and software engineering best practices.
• Collaborate with technical and non‑technical stakeholders across complex programmes.
• Identify technical, delivery, security, data privacy, and regulatory risks.
• Contribute to technical documentation, solution design, and delivery planning.
• Support AI implementation and scaling initiatives across complex environments.
• Lead and develop teams, fostering capability growth through mentoring, coaching, and creating a high‑performing environment.

Qualifications

• Strong Python and SQL experience.
• Applied AI engineering, ML engineering, or software engineering background.
• Experience with LLMs, RAG, embeddings, prompt engineering, or fine‑tuning.
• Exposure to LangChain, LangGraph, Agent Development Kit, or similar agent frameworks.
• Experience with vector databases such as Pinecone, Chroma, or similar.
• API development experience, ideally with FastAPI or similar frameworks.
• Knowledge of MLOps, LLMOps, CI/CD, or production deployment practices.
• Experience designing or supporting evaluation frameworks for AI or agentic systems.
• Experience working with modern data architectures and cloud platforms.
• Understanding of AI risk, governance, security, and regulatory considerations.
• Financial services experience within capital markets or broader banking environments.

This is a strong opportunity for an AI engineering professional who wants to work on high‑impact AI and data transformation programmes within complex financial services environments.

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