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- Tasks: Own and develop AI deployment infrastructure, ensuring reliable system integration and performance.
- Company: Leading tech organisation focused on innovative AI solutions.
- Benefits: Competitive salary, generous leave, pension scheme, and private medical insurance.
- Other info: Join a forward-thinking team and tackle complex challenges in AI deployment.
- Why this job: Shape the future of AI systems in a dynamic, remote-first environment.
- Qualifications: 3-5 years in software or data engineering with strong Python and SQL skills.
The predicted salary is between 100000 - 125000 £ per year.
A leading technology-focused organisation is seeking an experienced AI Deployment Engineer to join its growing AI and data function. This is a highly technical, hands-on role forming the backbone of the company’s AI deployment capability, responsible for taking AI-driven solutions from prototype through to fully scalable, production-grade systems.
Working closely with AI Strategists and product stakeholders, the AI Deployment Engineer will own the underlying infrastructure that enables AI systems to operate reliably across the business. The role is predominantly remote, with occasional on-site collaboration days in London.
Key Responsibilities:- Own and develop the data and integration infrastructure supporting AI deployments, including pipelines, storage and data delivery layers
- Design and implement robust integrations between AI solutions and core business systems (CRM, ERP, SaaS platforms and internal tools)
- Build and maintain APIs, webhooks and middleware to enable seamless system-to-system communication
- Take AI prototypes into production by hardening, scaling and optimising for reliability and performance
- Implement monitoring, logging and alerting across all deployed pipelines and AI services
- Manage data structures, schemas and transformation logic supporting ongoing and future AI initiatives
- Troubleshoot and resolve production issues, including integration failures and data inconsistencies
- 3-5 years experience in software engineering, data engineering, or similar infrastructure-focused roles
- Strong programming ability in Python and SQL, with experience building production-grade data pipelines
- Solid understanding of integration patterns including REST APIs, webhooks, OAuth and event-driven architectures
- Experience with orchestration tools such as Airflow, Prefect or Dagster
- Familiarity with cloud environments (AWS, GCP or Azure)
- Experience with containerisation tools such as Docker and Kubernetes
- Proven experience integrating multiple business systems and ensuring reliable data flow between platforms
- Strong troubleshooting skills with a focus on system reliability and data integrity
- Experience working with Microsoft 365 and exposure to AI productivity tooling is advantageous
- Vector databases and embedding-based pipelines
- Real-time data streaming technologies (e.g. Kafka, Flink)
- RPA tools such as UiPath or Power Automate
- Data transformation tools such as dbt
- Exposure to modern AI tooling and frameworks (e.g. Claude-based developer tools)
- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
- 25 days annual leave, rising to 28 with service
- Holiday buy/sell scheme with ability to carry over up to 10 days annually
- Pension scheme matched up to 5% (with salary sacrifice option available)
- Life assurance up to 9x annual salary
- Income protection covering up to 75% of salary
- Private medical insurance (including family cover option)
This is a senior technical role within a forward-thinking AI team, offering the opportunity to shape and scale production AI systems within a complex enterprise environment. The position is fully remote with occasional travel to London for collaboration sessions. The organisation encourages innovation, ownership, and technical excellence, making it ideal for an engineer who enjoys solving complex infrastructure and integration challenges at scale.
AI Deployment Engineer employer: Artis IT
Contact Detail:
Artis IT Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Deployment Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at tech meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving Python and SQL. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions related to AI deployment and integration patterns. Practise explaining your past projects and how you tackled challenges—this will help you shine during the interview.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace AI Deployment Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI Deployment Engineer role. Highlight your experience with Python, SQL, and any relevant cloud environments. We want to see how your skills match what we're looking for!
Showcase Your Projects: Include specific projects where you've built data pipelines or integrated systems. We love seeing real-world examples of your work, especially if they relate to AI solutions or production-grade systems.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for your skills and experiences to make it easy for us to read. We appreciate straightforward communication!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at Artis IT
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, SQL, and cloud environments like AWS or Azure. Brush up on your knowledge of REST APIs and integration patterns, as these will likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've troubleshot production issues or optimised data pipelines. Use the STAR method (Situation, Task, Action, Result) to structure your answers, highlighting how your actions led to improved system reliability and data integrity.
✨Understand the Company’s AI Vision
Research the company’s current AI initiatives and be ready to discuss how you can contribute to their goals. Showing that you understand their vision and can align your skills with their needs will set you apart from other candidates.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, the tools they use, and the challenges they face in AI deployment. This not only shows your interest but also helps you gauge if the company culture and role are a good fit for you.