At a Glance
- Tasks: Build cutting-edge AI solutions for top-tier banks and enhance customer experiences.
- Company: Join a leading consultancy at the forefront of AI in financial services.
- Benefits: Hybrid work, competitive salary, and opportunities for professional growth.
- Other info: Exciting roles available from AI Engineer to Senior Manager.
- Why this job: Make a real impact by embedding AI into critical banking operations.
- Qualifications: Strong background in software or data engineering with AI product experience.
The predicted salary is between 65000 - 80000 £ per year.
AI is becoming core infrastructure in Financial Services, not an experiment. We're partnering with a leading consultancy delivering AI and data programmes for Tier 1 banks, embedding AI into fraud, risk, compliance and customer journeys at scale.
What You'll Be Doing
- Build production-grade AI and GenAI solutions for global banking clients
- Develop LLM apps, RAG platforms and agentic workflows
- Deploy AI across fraud, risk, compliance and CX
- Integrate AI into existing banking platforms and data ecosystems
- Help shape scalable, governed AI operating models
What You'll Bring
- Strong software, platform or data engineering background
- Proven experience shipping AI products into production
- Financial services or regulated industry exposure
- Stakeholder skills - from engineers to senior leadership
- Levels Open AI Engineer through to Solution Architect, Principal Consultant and Senior Manager.
AI Engineer in Manchester employer: Datatech Analytics
Datatech Analytics is an exceptional employer, offering a dynamic work culture that prioritises innovation and collaboration within the secure government and defence sectors. Employees benefit from meaningful projects that have a direct impact on national security, alongside opportunities for professional growth and development in cutting-edge technologies. With a hybrid working model and a focus on employee well-being, this role provides a unique chance to contribute to critical transformation programmes while enjoying a supportive and engaging workplace.
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 Datatech Analytics 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 Datatech Analytics.
✨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 Datatech Analytics.
✨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 Datatech Analytics 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 Datatech Analytics.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Datatech Analytics 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 Datatech Analytics
✨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 Datatech Analytics 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.
