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., * 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, Senior .NET Engineer £65,000-£70,000 * Fully Remote UK * SaaS / PPM Sector I'm supporting a high-growth SaaS company in the Project Portfolio Management sector to hire a Senior .NET Engineer to join their remote-first UK engineering team. This role focuses on building..., Development Coach - AI (Level 3 & 4) Location: Remote-first (with occasional travel for team events or customer meetings) Reports to: Performance Manager - Delivery Contract: Full-time About Apprentify At Apprentify, we unlock talent and accelerate digital..., Job Description Senior Software Engineer (Algorithms & Computer Vision) - Liverpool An innovative technology company is seeking a Senior Software Engineer with strong experience in algorithms and computer vision to join its growing development team. This role will focus..., We are seeking an experienced Senior Primary Design Engineer to lead and deliver high-quality primary engineering designs for HV substations and power infrastructure projects. Working for the specialist power engineering arm of a FTSE 250 company, you will play a key role..., Senior Software Engineer | Remote | Django | SaaS UK Remote (Quarterly team meet-ups) £60,000-£70,000 (DOE) Tech Stack: - Python - Django - Authentication methods - OAuth2, JWT, API keys - AWS SR2 are partnering with a growing SaaS platform used by organisations..., Development Coach - AI Automation (Level 4) Location: Remote-first (with occasional travel for team events or customer meetings) Reports to: Performance Manager - Delivery Contract: Full-time About Apprentify At Apprentify, we unlock talent and accelerate digital...

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
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