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- Tasks: Design and build scalable AI infrastructure, develop robust systems in Python, and implement CI/CD pipelines.
- Company: Join a cutting-edge AI project focused on improving data quality with LLM technology.
- Benefits: Enjoy remote work flexibility and competitive pay of £550/day, outside IR35.
- Why this job: Be part of an innovative team driving impactful AI solutions in a collaborative environment.
- Qualifications: Proven experience with LLM features, strong Python skills, and familiarity with cloud platforms required.
- Other info: This role is initially for 3 months, with potential for extension based on project needs.
The predicted salary is between 39600 - 66000 £ per year.
We’re hiring for a cutting-edge AI project and looking for AI Software Engineer(s) with real-world experience building and deploying LLM-powered systems. The project is largely aimed at utilising LLMs to improve data quality and detect duplications in different data sets.
What You’ll Be Doing:
- Designing and building scalable AI/LLM infrastructure — APIs, microservices, orchestration layers.
- Developing robust systems in Python, with a strong grounding in software engineering best practices.
- Implementing CI/CD pipelines, Infrastructure-as-Code, and deploying to cloud (ideally Azure).
- Driving MLOps/LLMOps: versioning, tracking, monitoring, retraining — using tools like MLflow or W&B.
- Developing and optimising LLM features: prompt design, chaining, output handling, and cost/performance tuning.
What You’ll Need:
- Proven experience shipping LLM/AI features to production environments.
- Strong Python skills and experience working across full SDLC (Agile/Scrum).
- Practical knowledge of transformer architectures and LLM context strategies.
- Experience orchestrating multi-step AI workflows (sequential/parallel).
- Familiarity with cloud platforms (Azure preferred) and scalable system design.
- Hands-on with Git and modern MLOps practices.
- Databricks experience required.
If you have the required skills and experience, then please apply to discuss further.
AI Software Engineer employer: AI Connect
Contact Detail:
AI Connect Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Software Engineer
✨Tip Number 1
Familiarise yourself with the latest advancements in LLM technology and be prepared to discuss them during your interview. This shows your passion for the field and your commitment to staying updated.
✨Tip Number 2
Prepare examples of your previous work with LLMs, particularly any projects where you improved data quality or detected duplications. Real-world examples can make a strong impression.
✨Tip Number 3
Brush up on your Python skills and be ready to demonstrate your coding abilities. You might be asked to solve problems or write code snippets during the interview.
✨Tip Number 4
Understand the principles of MLOps and be prepared to discuss how you've implemented CI/CD pipelines in your past roles. This will highlight your practical experience and technical expertise.
We think you need these skills to ace AI Software Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with LLMs and AI systems. Focus on specific projects where you've designed scalable infrastructure or implemented CI/CD pipelines, especially in Python.
Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about AI and how your skills align with the job requirements. Mention your familiarity with tools like MLflow or W&B and your experience with cloud platforms, particularly Azure.
Showcase Relevant Projects: If you have worked on relevant projects, consider including a portfolio or links to your work. Highlight any experience with Databricks and your approach to optimising LLM features.
Proofread Your Application: Before submitting, carefully proofread your application for any errors. Ensure that your technical terminology is accurate and that your application reflects your best professional self.
How to prepare for a job interview at AI Connect
✨Showcase Your LLM Experience
Be prepared to discuss your real-world experience with LLM-powered systems. Highlight specific projects where you've built or deployed these systems, focusing on the challenges you faced and how you overcame them.
✨Demonstrate Your Python Proficiency
Since strong Python skills are essential for this role, be ready to talk about your experience with Python in detail. You might even want to prepare for a coding challenge or technical questions that assess your software engineering best practices.
✨Familiarise Yourself with CI/CD and MLOps
Understand the principles of CI/CD pipelines and MLOps, especially tools like MLflow or W&B. Be ready to explain how you've implemented these in past projects and how they contributed to the success of your AI solutions.
✨Prepare Questions About the Project
Show your interest in the project by preparing insightful questions. Ask about the specific goals of the AI project, the team structure, and how they measure success. This demonstrates your enthusiasm and helps you gauge if it's the right fit for you.
