AI Software Engineer

AI Software Engineer

Brighton 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 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

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 their own home. With a strong emphasis on professional development, you'll 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 prepared 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.

✨Tip Number 4

Practice explaining complex technical concepts in simple terms. As an AI Software Engineer, you'll need to communicate effectively with both technical and non-technical stakeholders, so being able to break down your work will be crucial.

We think you need these skills to ace AI Software Engineer

Proficiency in Python
Experience with LLM/AI feature deployment
Understanding of transformer architectures
Knowledge of CI/CD pipelines
Familiarity with Infrastructure-as-Code
Experience with cloud platforms (preferably Azure)
Ability to design scalable AI infrastructure
Hands-on experience with Git
Practical knowledge of MLOps/LLMOps
Experience with Databricks
Strong understanding of software engineering best practices
Ability to orchestrate multi-step AI workflows
Experience with Agile/Scrum methodologies
Skills in prompt design and output handling
Cost/performance tuning expertise

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 LLM features you've developed, such as prompt design or cost/performance tuning.

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 specific projects where you've built and deployed LLM-powered systems. Highlight the challenges you faced and how you overcame them, as this will demonstrate your real-world experience.

✨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, as this will show your capability in driving MLOps/LLMOps.

✨Prepare for Cloud and Scalable System Design Questions

Since familiarity with cloud platforms, particularly Azure, is preferred, brush up on your knowledge of deploying scalable systems. Be prepared to discuss your experience with cloud services and how you've designed systems to handle large datasets.

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