About this role
Based in London, the Software Engineer II, AI Enablement Team position at swap involves developing internal systems and cost tracking for artificial intelligence workloads. This role suits a software professional with generalist tendencies who enjoys autonomy and problem-solving across various technologies.
Role Overview
The Software Engineer II, AI Enablement Team position focuses on building infrastructure, developer tooling, and cost observability frameworks for artificial intelligence applications. The professional in this position will help scale agentic workflows and establish best practices for technology usage across the organization.
Key Responsibilities
Requirements
Nice to Have
Skills and Tools
About the Company
Swap operates an artificial intelligence-native infrastructure platform that connects backend business operations with storefront experiences for global commerce brands. The enterprise centralizes international operations, supports intelligent workflows, and provides real-time data for merchants across cross-border trade, tax compliance, returns, and demand planning. The corporate culture emphasizes clarity, creativity, shared ownership, diversity, and equality.
How to Apply
Interested candidates should visit the official company careers page to submit an application for this role.
Skills and tech stack
Questions candidates ask
Where is the job located?
The position is based in London.
What is the experience requirement?
Candidates need 2+ years of professional software engineering experience.
What kind of projects will the engineer work on?
The engineer will build cost observability tooling for LLM and agent workloads, design internal guardrails for agentic coding, evaluate AI vendors, and manage projects from scoping to production rollout.
Are specific programming languages required?
No, the company looks for individuals who focus on solving problems rather than working on a particular tech stack or set of languages.
What experience is considered a bonus?
Bonus qualifications include experience with LLM or agentic tooling, AI cost observability, and internal developer platforms.