AI Engineer at Address Intelligence
London SE1 9SE, , United Kingdom -
Full Time


Start Date

Immediate

Expiry Date

02 Dec, 25

Salary

80000.0

Posted On

02 Sep, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Information Technology/IT

Description

Role: AI Engineer (Enterprise Agentic AI Systems)
Location: London Bridge, London, UK
Work Setup: Hybrid (3 days/week in office - Tues, Weds, Thurs)
Type: Full-time, Permanent
Seniority: Mid to Senior Level
Start Date: ASAP (flexible for the right person)

How To Apply:

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Responsibilities

THE ROLE

As an AI Engineer, you’ll help define the core intelligence behind our agentic platform - designing systems that enable AI to interact meaningfully with complex business environments.
You’ll work at the intersection of natural language processing, data systems, and applied reasoning - helping shape how our agents interpret context, generate insight, and act. This isn’t prompt engineering, nor is this automation at scale. This is building infrastructure that allows AI to operate inside real businesses and deliver impact autonomously.
You’ll join early enough to shape the architecture, tooling, and direction of the platform - and with the support of a team that’s already moving fast. Expect ambiguity, ownership, and the opportunity to influence how AI gets built for real-world decision-making.
This is a role for a systems-minded, product-aware builder - someone who sees around corners, enjoys unsolved problems, and wants to help define what AI can do when deeply embedded in business operations.

WHAT YOU’LL DO

  • Design and deploy intelligent agent workflows that operate on real-time business data
  • Build the core orchestration layer that powers agent reasoning, memory, and decision logic
  • Collaborate with cross-functional teams to define agent tools and data interaction patterns
  • Develop backend systems and services that securely connect agents to enterprise data sources
  • Implement workflows that enable agents to deliver insight and take follow-up action
  • Define evaluation frameworks to measure agent performance, accuracy, and reliability
  • Own the full lifecycle of agent development - from design and testing to deployment and iteration
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