At a Glance
- Tasks: Design and manage AI deployment pipelines, ensuring reliability and scalability.
- Company: Globally renowned organisation with a focus on AI and data innovation.
- Benefits: Competitive salary up to £85,000, hybrid work model, and career growth opportunities.
- Other info: Collaborative environment with a focus on continuous improvement and innovation.
- Why this job: Join a dynamic team at the forefront of AI technology and make a real impact.
- Qualifications: Experience in AI systems, CI/CD pipelines, and cloud infrastructure management.
The predicted salary is between 85000 - 85000 £ per year.
A globally renowned organisation is seeking an AI Ops Engineer to join a growing AI and data function, taking ownership of the operational backbone that enables AI systems to run reliably, securely and at scale in production environments. This AI Ops Engineer role sits at the intersection of machine learning, cloud infrastructure and DevOps, supporting the full lifecycle of AI solutions from deployment through to ongoing optimisation.
The AI Ops Engineer position is well suited to an engineer who enjoys building resilient platforms, improving operational maturity and working closely with data scientists and software engineers to deliver production-grade AI capability.
Responsibilities for the AI Ops Engineer:- Design, build and operate deployment pipelines for AI models, prompts and supporting artefacts
- Own lifecycle management including versioning, promotion, rollback and retirement of AI solutions
- Implement monitoring and observability covering performance, usage, drift and data quality
- Ensure AI systems meet security, compliance and governance requirements
- Optimise inference performance, scalability and cost efficiency
- Manage infrastructure supporting training and inference including cloud platforms, containers and GPU resources
- Enable reproducibility through experiment tracking and artefact management
- Support incident response, root-cause analysis and resolution of AI-related failures
- Collaborate with data scientists and software engineers to design scalable, reliable machine learning infrastructure
- Develop and maintain CI/CD pipelines for machine learning workloads
- Maintain standards for version control, testing and technical documentation
- Work with cross-functional teams to integrate AI solutions into existing platforms and workflows
- Stay current with advancements in MLOps, DevOps and AI operations, driving continuous improvement
- Strong experience operating machine learning or AI systems in production environments
- Hands-on experience with CI/CD pipelines for data or ML workloads
- Experience managing cloud-based infrastructure for AI workloads
- Solid understanding of monitoring, observability and operational resilience
- Strong collaboration skills with the ability to work across engineering and data teams
- Experience supporting secure, compliant and well-governed systems
- Experience integrating Python-based services with modern front-end frameworks
- Familiarity with MLOps practices for deploying, monitoring and managing AI systems
- Exposure to large-scale enterprise data environments or knowledge management systems
- Understanding of Agile delivery practices and collaborative tooling
- Knowledge of data security, compliance and responsible AI principles
- Domain exposure within engineering or manufacturing environments
If you are an AI Ops Engineer looking to take ownership of AI operations within a complex, production-focused environment, please apply in the immediate instance.
Production AI Ops Engineer - Pipelines, Reliability & Scale employer: Involved Solutions
Join a globally renowned organisation that champions innovation and collaboration in the AI and data sector. With a hybrid working model based in Derby, employees benefit from a supportive work culture that prioritises professional growth and continuous learning, alongside competitive salaries and comprehensive benefits. This role offers the unique opportunity to work at the forefront of AI technology, contributing to impactful projects while enjoying a balanced work-life environment.
StudySmarter Expert Advice🤫
We think this is how you could land Production AI Ops Engineer - Pipelines, Reliability & Scale
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups or webinars, and connect with people 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 or GitHub repository showcasing your projects related to AI Ops, CI/CD pipelines, or cloud infrastructure. This gives potential employers a tangible look at what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions and scenarios related to AI systems and operational resilience. Practice explaining your thought process clearly, as collaboration is key in this role.
✨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 love seeing candidates who are proactive about their job search!
We think you need these skills to ace Production AI Ops Engineer - Pipelines, Reliability & Scale
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the job description. Highlight your experience with AI systems, CI/CD pipelines, and cloud infrastructure. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI Ops and how your background makes you a perfect fit for our team. Keep it engaging and relevant to the role.
Showcase Your Projects:If you've worked on any cool projects related to machine learning or AI, make sure to mention them! We love seeing real-world applications of your skills, especially if they demonstrate your ability to build resilient platforms.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Involved Solutions
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description. Brush up on your experience with CI/CD pipelines, cloud infrastructure, and monitoring tools. Being able to discuss specific projects where you've implemented these technologies will show your expertise.
✨Showcase Your Collaboration Skills
Since this role involves working closely with data scientists and software engineers, be prepared to share examples of how you've successfully collaborated in the past. Highlight any cross-functional projects you've been part of and how you contributed to their success.
✨Demonstrate Problem-Solving Abilities
Prepare to discuss challenges you've faced in previous roles, particularly around operational resilience and incident response. Use the STAR method (Situation, Task, Action, Result) to structure your answers and clearly illustrate how you tackled these issues.
✨Stay Current with Industry Trends
Familiarise yourself with the latest advancements in MLOps, DevOps, and AI operations. Being able to discuss recent trends or innovations in these areas during your interview will demonstrate your passion for the field and your commitment to continuous improvement.
