Applied AI Engineer

As an Applied AI Engineer in Direct Acquisition, you will design and build AI agents that automate core acquisition workflows. You will own end-to-end architecture, from planning monthly rounds to integrating with predictive models and data pipelines. Your work balances autonomous agent logic with human oversight, ensuring reliable, compliant decision-making in production. This role offers high-impact scope across direct mail campaigns and cross-functional collaboration with commercial, product, and compliance teams. You’ll shape how AI accelerates SME onboarding and growth at iwoca.

• Flexible working hours
• Medical insurance from Vitality
• Private GP service for you, partner, and dependents
• 25 days' holiday per year + birthday day off
• Sabbatical after four years
• 3% Pension contributions

• Design and build end-to-end AI agents and the surrounding system architecture
• Orchestrate processes with deterministic code and human-in-the-loop approvals
• Define memory, task management, access controls, and audit trails for agents
• Integrate agents with predictive models, data pipelines, and channel tools
• Measure agent performance, failures, costs, and business value
• Collaborate with Core Systems and Compliance on access and controls
• Own delivery of each agent from conception to in-production operation

• System ownership of complex end-to-end production systems
• Strong design judgment with ability to justify trade-offs
• Proven pace delivering in unfamiliar areas with reliable results
• Agent engineering experience involving LLMs with actions, not just chat
• Ability to implement permissions, data access rules, and audit trails
• Constructive challenge and cross-functional collaboration
• Experience leveraging AI coding tools and validating their outputs
• Clear written and verbal communication tailored to audiences

• clear, direct communication
• collaboration with commercial and product teams
• constructive challenge and problem-solving
• agent-based system design
• AI coding tools usage
• integration with data pipelines and predictive models