AI Engineer
abound · Shenzhen ·
- Category
- AI engineering
- Experience
- 1+ years
abound · Shenzhen ·
About Abound
We’re redefining consumer lending in the UK, and beyond. Using advanced AI and Open Banking data, we make fair, affordable personal finance available to more people. While traditional lenders rely almost entirely on credit scores, we look at the full financial picture - how much you spend, and what you can afford to repay to build a deeper, more accurate understanding of each customer's unique financial situation.
And we've shown it works at scale. We’ve issued over £1.3bn in loans directly to customers while delivering market-leading credit performance - for every 10 defaults the industry expects, we see only 3. We also reached profitability just 2.5 years after launch.
Backed by £2bn+ of funding from top-tier investors including Citi, GSR Ventures, and Deutsche Bank, we’re recognised as one of Europe’s fastest-growing fintechs (Sifted, CNBC). Now, we’re expanding into new markets and product lines - and we’re looking for ambitious people who want to learn fast, take ownership, and grow with us.
About The Role
We’re looking for a smart, curious, and practical AI Engineer to join our global team in our Shenzhen office. You’ll work on real-world Generative AI applications, AI agents, and Python-based automation solutions for the consumer lending industry. This role is ideal for someone who wants to turn AI capabilities into measurable business impact, not just build demos. You’ll collaborate closely with our UK and Shenzhen teams to explore, build, evaluate, and integrate AI into customer operations, internal automation, risk workflows, and lending operations.
What You’ll Be Doing
Build Generative AI and AI agent solutions for customer operations, internal automation, and lending operations
Design prompts, workflows, and evaluation processes to make AI systems more reliable and useful
Integrate LLMs with internal tools, APIs, databases, and business systems
Write clean, scalable, and maintainable Python code
Prototype quickly, test ideas, measure impact, and iterate based on real business needs
Collaborate with teams in the UK and Shenzhen to identify high-value AI use cases.
Help improve production reliability through testing, logging, monitoring, fallback handling, and human review where appropriate
Stay up to date with AI trends and propose practical ways to apply them in our business
Who you are
Ideally, 1-3 years of hands-on experience in software engineering, AI, machine learning, automation, or related technical work
Strong Python skills, including API integrations, data processing, async programming, and clean code practices
Solid understanding of Generative AI concepts, including LLMs, embeddings, RAG, prompt engineering, structured outputs, and model limitations
Familiar with prompt design patterns, evaluation methods, and techniques for improving reliability and reducing hallucination
Interested in AI agents and workflow design, including tool calling, task planning, memory, orchestration, and human-in-the-loop systems
Comfortable experimenting quickly, learning new tools, and turning ambiguous business problems into working solutions
Able to communicate clearly with both technical and non-technical teams
Fluent in English, including speaking, reading, and writing
Fluent in Mandarin, including speaking, reading, and writing
Ways To Stand Out From The Crowd
Practical LLM applications beyond simple chatbots or demos
Experience with RAG, embeddings, structured outputs, function calling, or agentic workflows
Understand how to evaluate AI outputs and improve reliability over time
Worked with cloud AI platforms such as GCP Vertex AI, AWS Bedrock, Azure OpenAI, or similar tools
Experience with financial services, consumer lending, credit risk, collections, or operations automation
Experience with AI coding tools, such as Claude Code, Codex, or Cursor
What We Value
Strong problem-solving ability
Curiosity about how AI systems work under the hood
Product sense and business awareness
Bias for action and fast learning
Ownership, pragmatism, and attention to quality