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- Tasks: Design and develop AI applications using Python and Databricks.
- Company: Join ScaleneWorks, a career architect connecting talent with top opportunities.
- Benefits: Hybrid work model, competitive salary, and professional growth.
- Other info: Collaborative environment with excellent career advancement opportunities.
- Why this job: Shape the future of AI while working on innovative projects.
- Qualifications: 7+ years in Python development with AI/GenAI experience.
The predicted salary is between 70000 - 90000 £ per year.
At ScaleneWorks People Solutions, we are looking for a Python AI Engineer with Databricks exposure for our well-known client.
Location: London, UK
Type of Work: Hybrid (2-3 days from the office in a week)
Employment Type: FTE (Full Time Employment) or Inside IR35 Contract
Overview: We are looking for a Python AI Engineer with hands-on experience in Generative AI, backend development, and database-driven applications. The role involves designing and building AI-enabled applications, developing APIs and services to deploy AI models, and integrating them with enterprise databases and cloud platforms. The candidate should be comfortable working across AI solution design, backend development, and data engineering.
Key Responsibilities:
- Design and develop AI and Generative AI applications using Python.
- Build backend services and APIs using Flask or Django for AI-powered systems.
- Work with enterprise databases (SQL-based systems) to ingest, transform, and manage large datasets.
- Develop and integrate GenAI capabilities such as LLM-powered workflows, AI assistants, or automation tools.
- Design scalable architectures for AI solutions including model deployment and data pipelines.
- Build REST APIs and microservices to integrate AI models with enterprise applications.
- Work with cloud platforms (Azure preferred) to deploy and scale AI applications.
- Collaborate with data engineers, product teams, and domain experts to build production-grade AI solutions.
Required Technical Skills:
- 7+ years of experience as a Python developer, with at least the last 3+ years focused on AI / GenAI solutions.
- GenAI / AI development experience: LLM applications, AI workflows, or AI-enabled automation.
- Python development: Strong coding and data processing experience.
- SQL and database experience: Querying, data modeling, and data integration.
- Backend frameworks: Django or Flask.
- API development: RESTful services and microservice architecture.
- AI system architecture / solution design: Designing scalable AI applications.
- Cloud platforms: Azure AI services preferred.
- Data platforms: Experience with Databricks or similar ML platforms is a plus.
Soft Skills:
- Strong problem solving and analytical thinking.
- Ability to work in cross-functional teams.
- Good communication and collaboration skills.
If you are ready to embark on an exciting journey with ScaleneWorks, we would love to hear from you! Submit your resume today and let’s unlock new possibilities together.
Python AI Engineer with Databricks in London employer: ScaleneWorks People Solutions LLP
Contact Detail:
ScaleneWorks People Solutions LLP Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Python AI Engineer with Databricks in London
✨Tip Number 1
Network like a pro! Reach out to people in your industry on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python AI projects, especially those involving Databricks. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common technical questions related to AI and backend development. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re here to support you every step of the way in landing that dream job!
We think you need these skills to ace Python AI Engineer with Databricks in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Python AI Engineer role. Highlight your experience with Databricks, Generative AI, and backend development to catch our eye!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a perfect fit for the role. Keep it engaging and personal.
Showcase Your Projects: If you've worked on any relevant projects, don’t hold back! Include links or descriptions of your work with AI applications, APIs, or cloud platforms. We love seeing what you can do!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity!
How to prepare for a job interview at ScaleneWorks People Solutions LLP
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills, especially in AI and Generative AI. Be ready to discuss your experience with frameworks like Flask or Django, and don’t forget to highlight any projects where you've built APIs or worked with Databricks.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex problems in past roles. Think about challenges you've faced in AI solution design or backend development, and be ready to explain your thought process and the outcomes.
✨Understand the Company’s Needs
Research ScaleneWorks and their client’s business model. Understand how your role as a Python AI Engineer fits into their vision. This will help you tailor your answers and show that you're genuinely interested in contributing to their success.
✨Practice Collaboration Scenarios
Since the role involves working with cross-functional teams, prepare for questions about teamwork. Think of instances where you collaborated with data engineers or product teams, and be ready to discuss how you communicated and resolved conflicts.