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- Tasks: Support deployment and configuration of AI-powered platforms across EMEA.
- Company: Join Fogsphere, a leader in AI, computer vision, and IoT innovation.
- Benefits: Work remotely with opportunities for international travel and professional growth.
- Why this job: Make a real impact by transforming safety and operations with cutting-edge technology.
- Qualifications: Experience in Linux, DevOps, and Kubernetes; strong communication skills.
- Other info: Dynamic role with hands-on technical challenges and customer engagement.
The predicted salary is between 36000 - 60000 £ per year.
As a Delivery Engineer at Fogsphere, you will support the deployment, configuration, and operation of Fogsphere’s AI‑powered platform across customer and partner environments in EMEA. You will work closely with Senior Delivery Engineers, partners, and enterprise customers to deploy production‑grade Kubernetes infrastructure, configure AI workflows, and integrate Fogsphere with external systems. This is a hands‑on, customer‑facing technical role, ideal for an engineer with a strong DevOps foundation who is looking to grow expertise in AI, computer vision, edge computing, and IoT. The position is based in London. Candidates located elsewhere will only be considered if they demonstrate exceptional skills and proven ability to succeed in this role. While most work will be performed remotely, the role may require international travel to customer sites in Europe and the Middle East.
Key Responsibilities
- Infrastructure Deployment & Operations: Support the deployment, configuration, and maintenance of Kubernetes clusters on cloud and bare‑metal environments (e.g. Azure AKS or equivalent). Deploy and operate containerized applications using Docker (or similar). Assist in deploying and managing edge nodes for real‑time AI inference. Monitor system performance, reliability, and availability across distributed environments. Collaborate with senior engineers on troubleshooting and operational improvements.
- AI Workflow Configuration: Configure and optimize AI workflows using Fogsphere’s no‑code platform. Tune computer vision parameters such as regions of interest (ROIs), thresholds, and filters. Learn and apply best practices for AI workflow deployment and optimization.
- Integrations & APIs: Support integrations with third‑party systems such as ERP, SCADA, safety, retail, or logistics platforms. Work with Fogsphere’s API‑driven platform for automation and reporting. Configure publish/subscribe messaging patterns (e.g. MQTT, Kafka, or similar technologies).
- Customer & Partner Enablement: Support customer and partner deployments across EMEA. Participate in technical onboarding, training sessions, and workshops. Provide clear, empathetic technical support to customers with varying levels of technical maturity. Contribute to technical documentation and deployment guides.
Required Skills & Experience
- 3–4 years of experience in Linux systems administration and DevOps.
- Hands‑on experience with Kubernetes in production environments.
- Strong understanding of containers and container orchestration (Docker, Kubernetes).
- Experience working with REST APIs and external systems.
- Basic understanding of distributed systems and cloud infrastructure.
- Strong written and verbal communication skills in English.
- A customer‑focused mindset with patience and empathy when supporting users.
Nice to Have
- Experience with Azure AKS or other managed Kubernetes services.
- Exposure to computer vision or AI‑based workflows.
- Familiarity with MQTT, Kafka, or event‑driven architectures.
- Experience with edge computing, IoT platforms, or sensors.
- Knowledge of LoRaWAN networks and devices.
- Additional languages such as Italian, Spanish, or Arabic.
- Proven experience in customer‑facing delivery or partner enablement roles.
Qualifications
- Bachelor’s or Master’s in Computer Science, Engineering, or equivalent experience.
- 2+ years in Linux, DevOps, and distributed infrastructure deployment.
- 2+ years of production Kubernetes experience.
Why Join Fogsphere
You’ll be at the forefront of AI, computer vision, and IoT innovation, working with global partners and leading enterprises in oil & gas, energy, manufacturing, smart cities, transportation & logistics, and retail. This role combines deep technical challenges with the opportunity to make a real impact by training and supporting partners in deploying AI to transform safety, security, and operations across EMEA.
Selection Process
After submitting your application, you will be contacted by our HR team to schedule an initial interview, subject to a positive CV screening. The first interview will focus on getting to know you, your background, and your career path, and will include a small number of light technical questions. If the outcome is positive, you will be invited to one or two technical interview rounds (depending on both your availability and the team’s schedule), aimed at assessing your technical skills and problem‑solving approach. Following a successful technical evaluation, you will have a final conversation with members of the management team. At that stage, you will be ready to move forward and start your journey with Fogsphere.
Seniority level: Associate
Employment type: Full‑time
Job function: Production
Industry: IT Services and IT Consulting
Junior–Mid Delivery Engineer (EMEA) in England employer: Fogsphere
Contact Detail:
Fogsphere Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Junior–Mid Delivery Engineer (EMEA) in England
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to Kubernetes, AI workflows, or any relevant tech. This gives potential employers a taste of what you can do beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions, especially around DevOps and customer support scenarios. Remember, they want to see how you think and solve problems!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining Fogsphere and being part of our exciting journey in AI and IoT.
We think you need these skills to ace Junior–Mid Delivery Engineer (EMEA) in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Kubernetes, DevOps, and any relevant AI projects. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the role at Fogsphere and how your background makes you a great fit. Keep it concise but impactful!
Showcase Your Technical Skills: In your application, mention specific tools and technologies you’ve worked with, like Docker or Azure AKS. We love seeing hands-on experience, so don’t hold back on the details!
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 get back to you quickly!
How to prepare for a job interview at Fogsphere
✨Know Your Tech Inside Out
Make sure you brush up on your Kubernetes and Docker skills. Be ready to discuss your hands-on experience with these technologies, as well as any challenges you've faced and how you overcame them. Fogsphere is looking for someone who can hit the ground running!
✨Showcase Your Customer-Focused Mindset
Since this role involves a lot of customer interaction, prepare examples that highlight your ability to provide empathetic technical support. Think about times when you've helped users with varying levels of technical knowledge and how you made their experience better.
✨Familiarise Yourself with AI Workflows
Dive into the basics of AI workflows and computer vision. Be prepared to discuss how you would configure and optimise these workflows using Fogsphere’s platform. Showing enthusiasm for learning and applying best practices will definitely impress the interviewers.
✨Prepare for Technical Questions
Expect some light technical questions in the first interview, but also be ready for deeper dives in later rounds. Brush up on your understanding of REST APIs, distributed systems, and cloud infrastructure. Practising problem-solving scenarios can help you feel more confident.
