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- Tasks: Design and build scalable AI infrastructure, develop robust systems, and optimise LLM features.
- 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 making a real impact in AI and data management.
- Qualifications: Proven experience with LLMs, 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. Being able to share specific outcomes will demonstrate your real-world experience.
✨Tip Number 3
Brush up on your Python skills and be ready to solve coding challenges related to AI/ML during the interview. Practising common algorithms and data structures can give you an edge.
✨Tip Number 4
Showcase your understanding of CI/CD pipelines and MLOps practices by discussing how you've implemented these in past projects. Highlighting your hands-on experience with tools like MLflow or W&B will set you apart.
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 Strong Cover Letter: In your cover letter, emphasise your hands-on experience with MLOps and cloud platforms like Azure. Mention any relevant tools you've used, such as MLflow or W&B, to demonstrate your practical knowledge.
Showcase Relevant Projects: Include a section in your application that details specific projects where you've shipped LLM/AI features to production. Highlight your role, the technologies used, and the impact of your work.
Proofread Your Application: Before submitting, carefully proofread your application for any errors or inconsistencies. A polished application reflects your attention to detail, which is crucial in software engineering.
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 understanding of software engineering best practices.
✨Familiarise Yourself with MLOps Tools
Make sure you know the ins and outs of MLOps tools like MLflow or W&B. Be ready to explain how you've used these tools in previous projects, particularly in versioning, tracking, and monitoring AI models.
✨Prepare for Cloud Platform Discussions
As familiarity with cloud platforms, especially Azure, is preferred, brush up on your knowledge of deploying applications in the cloud. Be prepared to discuss your experience with Infrastructure-as-Code and CI/CD pipelines.
