At a Glance
- Tasks: Design and implement AI solutions that enhance productivity and decision-making.
- Company: Dynamic tech firm focused on real-world AI impact.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Exciting career prospects in a fast-paced environment.
- Why this job: Join a team driving innovation in AI and make a tangible difference.
- Qualifications: Experience in AI/ML solutions and Agile delivery required.
The predicted salary is between 70000 - 90000 £ per year.
Are you passionate about building practical AI solutions that drive real-world impact across delivery, operations, and workforce management - not just theoretical proofs of concept?
What you'll be doing:
- Designing and implementing AI and machine learning solutions that enhance productivity, automation, and decision-making.
- Identifying and refining AI use cases across Agile delivery, workforce management, and operational processes.
- Embedding generative AI capabilities such as copilots and chatbots into everyday enterprise workflows.
- Defining and enforcing ethical AI usage, governance, and compliance aligned to organisational standards.
- Architecting and optimising Agile tooling ecosystems using platforms such as Azure DevOps, Jira, GitHub, Jenkins, Clarity, and Rally.
- Rationalising and standardising tooling, taxonomies, and end-to-end reporting and MI across multiple delivery teams.
What we're looking for:
- Strong track record designing and delivering AI/ML solutions in an enterprise environment.
- Experience applying AI within Agile delivery, operations, or workforce management contexts.
- Background in large-scale enterprise transformations in financial services or similar regulated environments.
- Hands-on expertise with Jira, Clarity, Rally and related ecosystems, including consolidation and standardisation.
- Experience architecting integrated Agile toolchains with platforms such as Azure DevOps, GitHub, and Jenkins.
- Proven ability to embed end-to-end reporting and management information across complex delivery landscapes.
- Deep understanding of Agile frameworks such as Scrum, SAFe, and Kanban.
- Solid knowledge of the software development lifecycle and DevOps practices, including CI/CD.
Interested? Apply now for immediate consideration!
AI Architect in Burnley employer: Henderson Scott
As an AI Architect at our London-based firm, you'll be part of a dynamic team that thrives on innovation and collaboration, with a strong focus on practical AI solutions that make a tangible difference. We offer a hybrid work model that promotes work-life balance, alongside opportunities for professional growth in a supportive environment that values ethical AI practices and continuous learning. Join us to be at the forefront of AI technology while enjoying the unique advantages of working in one of the world's most vibrant cities.
StudySmarter Expert Advice🤫
We think this is how you could land AI Architect in Burnley
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. 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 AI and machine learning projects. This could be anything from personal projects to contributions to open-source. It’s a great way to demonstrate your expertise beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on common AI/ML scenarios and case studies. Be ready to discuss how you've tackled real-world problems using AI solutions. Practice makes perfect, so consider mock interviews with friends or mentors.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for passionate individuals who want to make an impact. Plus, applying directly can sometimes give you a leg up in the hiring process.
We think you need these skills to ace AI Architect in Burnley
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with AI and machine learning solutions. We want to see how you've made a real-world impact, so don’t just list your skills—show us how you’ve applied them in previous roles!
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 aligns with our needs. We love seeing enthusiasm and a clear understanding of the role.
Showcase Relevant Projects:If you've worked on any projects that involved Agile delivery or embedding AI capabilities, make sure to mention them. We’re keen to see practical examples of your work, especially in enterprise environments.
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Henderson Scott
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI and machine learning solutions. Be ready to discuss specific projects you've worked on, especially those that had a real-world impact. This will show your passion and expertise in the field.
✨Understand Agile Frameworks
Familiarise yourself with Agile methodologies like Scrum, SAFe, and Kanban. Be prepared to explain how you've applied these frameworks in past roles, particularly in relation to AI and operational processes. This will demonstrate your ability to integrate AI into existing workflows.
✨Showcase Your Tooling Experience
Highlight your hands-on experience with tools like Jira, Azure DevOps, and GitHub. Discuss how you've used these platforms to architect integrated toolchains and improve productivity. This will help the interviewers see your practical skills in action.
✨Ethics Matter
Be ready to talk about ethical AI usage and governance. Share your thoughts on compliance and how you've ensured ethical standards in your previous projects. This shows that you not only care about innovation but also about responsible AI practices.
