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# AI Engineer

- **Company:** Experienced Consultants
- **Location:** London, United Kingdom
- **Salary:** £59,102
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Automated Storage and Retrieval Systems, Databases, Information Engineering, Data Governance, Graph Database, Python (Programming Language), Search Technologies, Unstructured Data, Retrieval-Augmented Generation, Multi-Agent Systems, IT Architecture, Agentic-AI, Performance Monitor
- **Published:** November 12, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5962869588

## About the Role

* - Strong experience in software, AI or data engineering, including the design and delivery of production-grade solutions.
 * - Proven track record of building and deploying agentic AI systems in production environments.
 * - Strong Python development and API integration experience.
 * - Experience with knowledge graphs, semantic search and retrieval systems.
 * - Familiarity with MCP and related tool integration standards.
 * - Experience deploying solutions on AWS or GCP.

## Description

We are looking for an experienced consultant who can design the architecture, build working systems, and take them from demo to a scaled, governed deployment inside a regulated financial institution. This is a hands-on build role, not an advisory one. The successful candidate will combine practical agentic AI engineering with knowledge graph and entity-resolution experience, and will be comfortable operating within a bank's control environment.
Key Responsibilities Architecture design

 * - Design and deploy agentic AI workflows to automate investment sourcing, market research, due diligence and document generation.
 * - Design and maintain a venture intelligence knowledge graph covering companies, founders, investors and transactions.
 * - Define AI architecture, data governance, provenance and quality standards across internal and external data sources.

Agent development

 * - Develop AI agents to analyse companies, markets and investment opportunities using structured and unstructured data.
 * - Build automated diligence workflows that extract, validate and synthesise information from pitch decks, financials, research reports and industry databases.
 * - Develop portfolio intelligence capabilities to monitor performance, financing activity, competitive developments and strategic risks.
 * - Integrate with approved internal and external data sources, including CRM, market data and portfolio management platforms.

Production and governance

 * - Deploy and optimise RAG, agent orchestration and knowledge graph services within the bank's approved technology environment.
 * - Implement monitoring and evaluation frameworks covering accuracy, quality, cost and operational performance.
 * - Ensure solutions are secure, auditable and reproducible.