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- Tasks: Design and build cutting-edge AI tools and secure integrations for enterprise systems.
- Company: Join a leading tech firm focused on innovative AI solutions.
- Benefits: Competitive daily rates, flexible work arrangements, and opportunities for professional growth.
- Other info: Collaborate with diverse teams to enhance AI platform adoption.
- Why this job: Shape the future of enterprise AI in a dynamic, engineering-driven environment.
- Qualifications: Strong Python skills and experience with LLMs and API development.
The predicted salary is between 72000 - 108000 £ per year.
I'm looking for an experienced ML Engineer to join a central AI engineering function responsible for building and scaling enterprise-grade agentic AI capabilities across a global organization. This team owns the core AI enablement platform used internally to support AI agents, orchestration workflows, knowledge retrieval, and secure tool integration at scale. The environment is highly engineering-focused, combining platform thinking with hands-on AI delivery.
The role will involve designing and building MCP servers, AI tools, orchestration skills, and secure API integrations that expose enterprise systems safely to LLM-powered agents. You'll also contribute to agent planning, tool-calling frameworks, RAG architecture, and the broader developer experience for internal AI platform adoption.
Key requirements:- Strong Python engineering experience
- Experience with LLMs, AI agents, and agentic reasoning patterns
- FastAPI and REST API development
- RAG and prompt engineering experience
- Kubernetes / containerisation knowledge
- Exposure to MCP or similar AI tooling frameworks
- Ability to work across platform and product engineering teams
This is an opportunity to help shape the future of enterprise AI infrastructure within a large-scale, modern engineering environment focused on governance, scalability, and production-quality AI systems.
ML Engineer employer: Tec Partners
Contact Detail:
Tec Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with other ML Engineers. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and AI tools. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and API development skills. Practice coding challenges and be ready to discuss your experience with Kubernetes and containerisation – these are hot topics right now!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications that way!
We think you need these skills to ace ML Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your strong Python engineering experience and any relevant work with LLMs and AI agents. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the opportunity at StudySmarter and how your experience with FastAPI, REST APIs, and Kubernetes makes you a perfect fit for our team.
Showcase Your Projects: If you've worked on any projects involving agentic reasoning patterns or RAG architecture, make sure to mention them. We love seeing practical examples of your work that demonstrate your hands-on experience in AI delivery.
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at Tec Partners
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills and be ready to discuss your experience with LLMs and AI agents. Be prepared to dive deep into your past projects, especially those involving FastAPI, REST APIs, and Kubernetes. The more specific examples you can provide, the better!
✨Showcase Your Problem-Solving Skills
During the interview, expect to tackle some technical challenges or case studies. Think about how you've approached complex problems in the past, particularly around orchestration workflows and secure API integrations. Demonstrating your thought process will impress the interviewers.
✨Understand the Company’s Vision
Research the company’s AI initiatives and their approach to agentic AI platforms. Being able to articulate how your skills align with their goals will show that you're genuinely interested in the role and understand the bigger picture of enterprise AI infrastructure.
✨Prepare Questions That Matter
Have a list of insightful questions ready to ask at the end of the interview. Inquire about the team dynamics, the tools they use for RAG architecture, or how they envision the future of their AI platform. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.