AI Engineer
AI in this role
ABOUT THE ROLE
We are looking for forward-thinking, high-performing AI Engineers who are excited to pioneer the future of AI-driven engineering at Paysend. In this role, you will work hands-on with Claude Code and the Anthropic API to design, harden, and ship agentic systems that write, review, test, and deploy code. This is a high-impact, build-and-own opportunity: you will take cutting-edge AI prototypes and turn them into resilient production infrastructure - directly empowering our global engineering teams, accelerating our product velocity, and helping us solidify Paysend as the definitive end-to-end payment infrastructure for the modern world.
THE ENGINEERING PROBLEM
The problem is not to make an LLM generate code. The problem is to make AI-assisted and agentic software delivery reliable enough to become part of normal engineering work.
These systems operate inside real software delivery workflows. They need to deal with incomplete context, failed execution, incorrect assumptions, external dependencies, changing repository state, and cases where an agent should not continue on its own. This means designing clear execution boundaries, decision points, observability, recovery and escalation paths, not only the agent behaviour itself.
The role includes shaping how these systems work, not only implementing integrations with existing AI tools.
WHAT YOU'LL DO
Design end-to-end AI-assisted delivery workflows, including agent responsibilities, execution boundaries, decision points, human intervention, failure handling, recovery, and escalation
Design and refine AI-driven pipelines that automate coding, code review, testing, and deployment tasks
Build and optimise agentic workflows using Claude Code and the Anthropic API, including custom tooling, MCP server integrations, sub-agents, and stateful orchestration logic
Engineer robust prompts, benchmark suites, and automated eval datasets; measure and improve pipeline accuracy, latency, and API costs
Define workflow-specific success criteria and operational evidence, including correctness, reliability, intervention and escalation rates, failure modes, and recovery effectiveness
Integrate core Anthropic capabilities (tool use, structured outputs, prompt caching, batch processing) into internal developer platforms
Handle unglamorous production work: sandboxed execution, strict error handling, retries, observability, guardrails, and edge cases
Own these systems after initial implementation: observe how they behave in real engineering workflows, investigate failures and incorrect behaviour, and improve the system based on operational evidence
Partner with engineers across the org to identify automation opportunities and roll out agentic tools safely with human-in-the-loop review mechanisms
WHAT WE'RE LOOKING FOR
Strong software engineering background, with experience designing, building, and operating production systems, and strong hands-on experience with Python or TypeScript
Ability to decompose end-to-end engineering workflows, identify decision boundaries, failure modes, dependencies, observability needs, and recovery paths
Direct, hands-on experience with Claude Code—you've used it beyond casual experimentation and understand its strengths, limits, and configuration (CLAUDE.md, sub-agents, hooks)
Experience building with LLM APIs: prompt engineering, tool/function calling, structured outputs, context window optimization, agentic loops, and evaluation
Familiarity with MCP (Model Context Protocol) server integration and custom workflows
Comfort turning prototypes into production systems: CI/CD integration, containerized execution, reliability engineering, and monitoring
Pragmatic judgment about where AI automation helps and where traditional deterministic logic or human oversight is required
NICE TO HAVE
Experience with agent orchestration frameworks or building custom agent harnesses/tooling
Track record shipping internal developer platforms or CLI tooling
Contributions to open-source AI frameworks, developer tools, or MCP servers
Why Join Paysend?
Make a Global Impact:
Join a company that is transforming how people and businesses move money around the world. Your work will contribute to products and services that help millions of customers stay connected globally.
Own Meaningful Outcomes:
We empower our people to take ownership, make decisions, and drive real impact. You'll have the opportunity to shape solutions, challenge the status quo, and see the results of your work firsthand.
Grow with Us:
As a fast-growing global fintech, we offer opportunities to learn, develop new skills, take on new challenges, and advance your career across functions and geographies.
Collaborate with Exceptional People:
Work alongside talented colleagues from diverse backgrounds and disciplines who are united by a shared ambition to build, innovate, and deliver great outcomes for our customers.
Move Fast and Make Things Happen:
We value action, curiosity, and continuous improvement. You'll be part of a culture that encourages experimentation, embraces change, and focuses on delivering meaningful results.
Be Part of Our Journey:
We're building the future of the global money movement. Join us at an exciting stage of growth where your ideas, expertise, and contributions can help shape what's next.
How we rate this
AI Engineer at Paysend rates 88 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a workflow you automated with AI tools, end to end.
- What's a project where you used Claude hands-on?
- Walk me through how you've used Anthropic in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Prompt engineering, AI agents, AI Automation, Claude, and Anthropic. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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