AI Software Engineer

AI Software Engineer

Worcester Freelance 39600 - 66000 £ / year (est.) Home office possible
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At a Glance

  • 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 is a 3-month contract role, ideal for tech-savvy individuals eager to advance their careers.

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

Join a forward-thinking company that values innovation and collaboration, offering AI Software Engineers the chance to work on groundbreaking projects from the comfort of your home. With a strong emphasis on professional development, you will have access to resources that foster growth in cutting-edge technologies, while enjoying a flexible work culture that prioritises work-life balance. This role not only provides competitive compensation but also the opportunity to contribute to meaningful advancements in AI, making it an ideal environment for those passionate about technology and its impact.
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Contact Detail:

AI Connect Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land AI Software Engineer

✨Tip Number 1

Make sure to showcase your real-world experience with LLM-powered systems during any conversations. Be ready to discuss specific projects where you've successfully implemented AI features, as this will demonstrate your hands-on expertise.

✨Tip Number 2

Familiarise yourself with the latest trends in MLOps and LLMOps. Being able to speak knowledgeably about tools like MLflow or W&B can set you apart from other candidates and show that you're up-to-date with industry practices.

✨Tip Number 3

Prepare to discuss your experience with cloud platforms, particularly Azure. Highlight any projects where you've deployed scalable systems, as this is a key requirement for the role and will demonstrate your capability to handle the infrastructure side of things.

✨Tip Number 4

Be ready to explain your approach to developing and optimising LLM features. Discussing your strategies for prompt design, output handling, and performance tuning will show that you have the practical knowledge needed for this position.

We think you need these skills to ace AI Software Engineer

Python Programming
Software Engineering Best Practices
API Development
Microservices Architecture
CI/CD Pipeline Implementation
Infrastructure-as-Code
Cloud Deployment (Azure preferred)
MLOps/LLMOps Practices
Versioning and Tracking Tools (e.g., MLflow, W&B)
LLM Feature Development
Prompt Design and Chaining
Cost/Performance Tuning
Agile/Scrum Methodologies
Transformer Architectures Knowledge
Multi-step AI Workflow Orchestration
Git Proficiency
Databricks Experience

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 hands-on experience with tools like MLflow or W&B, and your familiarity with Azure.

Showcase Relevant Projects: If you have worked on relevant projects, consider including a portfolio or links to your GitHub. Highlight any contributions to open-source projects or personal projects that demonstrate your expertise in LLMs and MLOps.

Proofread Your Application: Before submitting, carefully proofread your application for any errors or typos. A well-presented application reflects your attention to detail, which is crucial in software engineering roles.

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.

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