Back-End Software Engineer

You'll work on the core AI systems that make fraud decisions. This means building and improving the agent pipelines that coordinate LLMs, VLMs, OCR and forensic tools. You won't be just calling APIs, but designing how autonomous agents reason about complex, ambiguous evidence.

Day to day, you might be:

• Improving how the system handles a document type it's getting wrong
• Designing a new agent reasoning pattern (e.g., cross-referencing findings across multiple documents in a claim)
• Debugging why an agent produces inconsistent verdicts on edge cases
• Deploying pipeline changes to AWS and monitoring real-world performance
• Writing tests that verify an agent makes the right routing decision when evidence conflicts

The work sits at the intersection of AI engineering, systems design, and a surprisingly interesting fraud detection domain.

Builder Mindset

We're looking for people who build systems, not just talk about them.

This role is about shipping reliable AI into production: debugging edge cases, improving pipelines, and learning from real-world behaviour. If you enjoy turning ideas into working software and iterating quickly, you'll fit right in., Applied AI Software Engineer - LangChain, LangGraph, RAG, Knowledge Graphs A high-growth, technology-led scale-up (backed by a global leading organisation) is expanding its engineering capability following a highly successful 2025. As part of significant continued..., Were building out an AI Foundry capability and have four senior contract hires landing: AI Design Analyst shaping high value AI and Copilot use cases, mapping workflows, prompts and human in the loop models, embedding responsible AI and ISO42001 from design. AI Product..., Role: AI Specialist (AI Foundry) All potential applicants are encouraged to scroll through and read the complete job description before applying. Contract: 3 Months Rolling Location: Leeds, UK (Hybrid) Rate: £500 per day We are currently looking for an experienced AI..., Mobile Senior Air Conditioning Engineer - Yorkshire - National HVAC Contractor: Commercial CBW Staffing Solutions have an exciting role to join a growing Air Conditioning & Mechanical Engineering specialist who is looking to expand their operation due to the acquisition of...

You should be strong in:

• Python: you write clean, typed code and care about it working correctly at the edges
• Working with LLMs beyond chat: structured output, multi-step reasoning, prompt calibration for reliability
• AWS: comfortable with S3, Lambda, IAM, and deploying services that need to work without you watching them
• LLM/VLM Observability (e.g Arize Phoenix)
• Testing code that involves non-deterministic systems

Ideally you also bring:

• Experience with agent orchestration frameworks (LangGraph, LangChain, or similar)
• Familiarity with vision-language models for image analysis
• Some exposure to document analysis, OCR, or fraud detection
• Opinions about when agents are useful and when they're over-engineering, Job Description AI Engineer - Greenfield AI Project - Leeds (Hybrid)Up to £35,000My client is seeking Graduates with 18 months+ commercial software experience with an interest in AI, ideally some exposure through personal projects or commercial exposure. ABOUT THE..., Job Description Trainee AI Engineer - No Experience Needed! Ready to launch a future-proof career in AI - even if you have zero experience? We're looking for ambitious individuals ready to break into the world of artificial intelligence and data science. Our..., Job Description * Proven experience applying deep technical expertise across AI, ML, LLMs, agentic AI, and applied AI engineering, driving the design, evaluation, and governance of advanced AI solutions * Proven experience designing, evaluating and governing multi-agent...

We don't expect you to know all of:

• The specific AWS services we use (Bedrock AgentCore, EventBridge)
• Our domain (insurance fraud, document forensics)
• The exact frameworks in our stack

These are learnable. What matters more is that you can reason about systems, write reliable code, and think critically about how AI makes decisions.

How We Work

• Small team, high autonomy, async-first
• Security-conscious by default. We assume all inputs are hostile
• We'd rather halt and ask a question than ship something we're uncertain about
• Code gets attacked before it ships. We review from the perspective of a hostile auditor
• We don't over-engineer. Three similar lines of code is better than a premature abstraction

What Growth Looks Like

Early on: You're deploying changes to the pipeline, understanding how evidence flows through agents, and shipping features that touch the reasoning layer.

Later: You own major subsystems. The document analysis agent, the tool orchestration layer, or the cross-document case analysis pipeline. You're making architectural decisions about how agents reason.

Longer term: You're designing novel multi-agent patterns, integrating new forensic tools, and shaping how the platform learns from analyst feedback over time. Similar jobs

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