At a Glance
- Tasks: Design and deploy innovative AI solutions while collaborating with product teams.
- Company: Join ClearRoute, a forward-thinking engineering consultancy focused on quality and innovation.
- Benefits: Enjoy a hybrid work model, competitive salary, and a supportive work-life balance.
- Other info: Diverse and inclusive culture that values individuality and supports flexible working.
- Why this job: Make a real impact in AI and help transform organisations with your creativity.
- Qualifications: Strong Python skills, experience with LLMs, and a passion for problem-solving.
The predicted salary is between 60000 - 80000 £ per year.
About Us: ClearRoute is an engineering consultancy bridging Quality Engineering, Cloud Platforms and Developer Experience. We help enterprises reliably bring high-impact digital products to market faster, cheaper, and safer, working with technology leaders facing complex business challenges. We take as much pride in our people, culture and work-life balance as we do in making better software. We’re not just making better software. We’re making the making of software better. Collaborative, entrepreneurial and dedicated to problem solving, we bring the step change our customers need to sustain innovation. Our values challenge us to do the best we can for ClearRoute, our customers and most importantly our team. This is an opportunity for you to build the organisation from the ground up, use your voice to drive change and help transform organisations and problem domains. We work in a hybrid way, with two days a week working in our offices in either London or Manchester.
Role: We are looking for an AI/ML Engineer who can be responsible for designing, building, and deploying agentic AI solutions, working closely with product and client teams to bring use cases into production.
Key Responsibilities:
- Prototype and iterate on AI use cases rapidly
- Develop and implement agentic workflows
- Integrate LLMs, APIs, and data pipelines into scalable solutions
- Collaborate with PMs and stakeholders to refine requirements
- Ensure model performance, reliability, and monitoring
- Contribute to best practices in AI engineering and MLOps
Required Experience:
- Strong Python with agent frameworks
- Experience with LLMs and prompt engineering
- Solid understanding of data pipelines and APIs
- Experience deploying models in production environments
- Familiarity with cloud platforms (AWS/Azure/GCP)
- Strong problem-solving and collaboration skills
Desirable Experience:
- Knowledge of vector databases and retrieval-augmented generation (RAG)
- Exposure to MLOps tooling (CI/CD, monitoring, model versioning)
- Experience in regulated industries (e.g. utilities, energy)
At ClearRoute, we believe diverse perspectives lead to better outcomes, and inclusion creates the conditions for everyone to thrive. We are proud to have built a family friendly working environment and have many employees who have caring responsibilities alongside work. We welcome applications from people who require flexibility and will be happy to discuss needs on an individual basis. We are committed to fostering a culture where all team members feel respected, supported, and empowered to do their best work. We celebrate individuality and our differences and understand that some differences may mean that you require changes made to the interview process. We are happy to cater to your needs to make the interview accessible, if this is something you require please let us know by emailing us at join@clearroute.io
AI Engineer in Manchester employer: ClearRoute
At ClearRoute, we pride ourselves on fostering a collaborative and inclusive work culture that prioritises employee well-being and professional growth. As an AI Engineer, you will have the opportunity to shape innovative solutions while working in a hybrid environment that values flexibility and work-life balance. With a commitment to diversity and support for individual needs, ClearRoute is an excellent employer for those seeking meaningful and rewarding careers in technology.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer in Manchester
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at ClearRoute or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to ClearRoute.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like ClearRoute.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like ClearRoute that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace AI Engineer in Manchester
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at ClearRoute.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at ClearRoute and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at ClearRoute
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If ClearRoute uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
