At a Glance
- Tasks: Design and deploy LLM-powered tools, prototyping end-to-end systems.
- Company: Join an innovative startup focused on cutting-edge AI solutions.
- Benefits: Enjoy remote-first work, competitive salary, and a dynamic team culture.
- Other info: Engage in a structured interview process with hands-on challenges.
- Why this job: Be at the forefront of AI technology with impactful projects and a collaborative environment.
- Qualifications: Strong Python skills, 3-4+ years in software or ML engineering, and experience with AI tooling.
The predicted salary is between 42000 - 84000 € per year.
Overview
We are working with a motor insurance company who are investing heavily in AI-driven automation to scale inhouse operations. You will work closely with engineering, operations, and compliance teams to identify business problems and apply AI pragmatically, ensuring solutions are secure, explainable, and compliant. This is a hands-on role with strong influence over technical direction and AI best practices.
Role
AI Engineer - Lincolnshire
Responsibilities
- Design and implement AI-driven solutions across core business workflows
- Deliver production-grade AI use cases including:
- Contact centre transcription and summarisation (human-in-the-loop)
- Automated account summaries (payments, vulnerabilities, key facts)
- Deal payout validation across complex document sets
- Work with multiple LLMs (e.g. GPT, Gemini) and evaluate model quality
- Implement governance and validation layers to ensure factual accuracy and compliance
Essential
- Strong software engineering background
- Experience with Python and/or TypeScript
- Hands-on experience building AI or LLM-powered systems
- Understanding of AI governance, validation, or human-in-the-loop processes
- Experience working with cloud platforms (preferably Azure)
Desired Skills and Experience
- LLMs, RAG, Docker
AI Engineer employer: Harnham
Join a dynamic start-up that champions innovation and creativity in the AI space, offering a remote-first work environment tailored for UK-based talent. With a strong emphasis on employee growth, you will have the opportunity to work alongside industry experts, engage in meaningful projects, and contribute to cutting-edge LLM-powered tools. Enjoy a collaborative culture that values your input and fosters professional development, making it an ideal place for those seeking a rewarding career in AI engineering.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer
✨Tip Number 1
Familiarise yourself with the latest advancements in LLMs and RAG pipelines. Being able to discuss recent developments or projects you've worked on in this area will show your passion and expertise during the interview.
✨Tip Number 2
Prepare to demonstrate your Python skills through practical examples. Think of specific projects where you’ve built or deployed microservices, as this will be crucial for the technical challenge.
✨Tip Number 3
Brush up on your knowledge of CI/CD pipelines and modern software practices. Be ready to explain how you’ve implemented these in past roles, as it will likely come up in discussions with the Lead Data Scientist.
✨Tip Number 4
Showcase your experience with multimodal data by preparing examples that highlight your ability to work with text, images, and structured data. This will help you stand out as a candidate who can handle diverse document types effectively.
We think you need these skills to ace AI Engineer
Some tips for your application 🫡
Understand the Role:Before applying, make sure you fully understand the responsibilities of an AI Engineer as described in the job listing. Familiarise yourself with LLMs, RAG pipelines, and agent-based reasoning to tailor your application effectively.
Highlight Relevant Experience:In your CV and cover letter, emphasise your strong Python skills and any experience you have with AI tooling. Be specific about your work with microservices, CI/CD pipelines, and document extraction to demonstrate your fit for the role.
Showcase Your Projects:If you've worked on relevant projects, especially those involving multimodal data or MLOps, include them in your application. Provide links to your GitHub or portfolio to give the hiring team a clear view of your capabilities.
Prepare for the Interview Process:Anticipate the types of questions you might face during the intro chat and final interview. Brush up on your technical knowledge and be ready to discuss your approach to structuring AI software, as well as your past experiences in detail.
How to prepare for a job interview at Harnham
✨Showcase Your Python Skills
Since strong Python engineering skills are crucial for the role, be prepared to discuss your experience with Python in detail. Bring examples of projects where you've used Python for AI tooling, and be ready to explain your thought process and problem-solving approach.
✨Demonstrate Your Microservices Knowledge
Familiarity with microservices is key for this position. Be ready to talk about your experience with FastAPI and Kubernetes. Consider preparing a brief overview of a project where you successfully built and deployed a microservice, highlighting any challenges you faced and how you overcame them.
✨Prepare for Technical Challenges
The take-home technical challenge will focus on structuring AI software. Brush up on best practices for building scalable and maintainable code. Practise coding problems that involve document extraction and reasoning, as these will likely be relevant to the challenge.
✨Engage with the Team During the Deep Dive
In the final stage interview, you'll have a deep dive with the wider team. Prepare thoughtful questions about their current projects and technologies they use. This shows your genuine interest in the role and helps you assess if the company culture aligns with your values.
