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- Tasks: Support deployment and operation of AI-powered platforms across EMEA with hands-on technical work.
- 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: 3-4 years in Linux systems and DevOps, with Kubernetes experience.
- Other info: Dynamic role with excellent career advancement in a collaborative environment.
The predicted salary is between 36000 - 60000 Ā£ per year.
As a Delivery Engineer at Fogsphere, you will support the deployment, configuration, and operation of Fogsphere's AIāpowered platform across customer and partner environments in EMEA. You will work closely with Senior Delivery Engineers, partners, and enterprise customers to deploy productionāgrade Kubernetes infrastructure, configure AI workflows, and integrate Fogsphere with external systems. This is a handsāon, customerāfacing 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 bareāmetal environments (e.g. Azure AKS or equivalent).
- Deploy and operate containerized applications using Docker (or similar).
- Assist in deploying and managing edge nodes for realātime 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 noācode 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 thirdāparty systems such as ERP, SCADA, safety, retail, or logistics platforms.
- Work with Fogsphere's APIādriven 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
- 3ā4 years of experience in Linux systems administration and DevOps.
- Handsāon 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 customerāfocused 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 AIābased workflows.
- Familiarity with MQTT, Kafka, or eventādriven 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 customerāfacing 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 will 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 problemāsolving 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.
Mid Delivery Engineer (EMEA) in London employer: Fogsphere
Contact Detail:
Fogsphere Recruiting Team
StudySmarter Expert Advice š¤«
We think this is how you could land Mid Delivery Engineer (EMEA) in London
āØTip Number 1
Network like a pro! Reach out to current or former employees at Fogsphere on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can double your chances of landing that interview.
āØTip Number 2
Show off your skills in action! If youāve got a GitHub or personal project showcasing your Kubernetes or AI workflow skills, make sure to share it during interviews. Itās a great way to demonstrate your hands-on experience.
āØTip Number 3
Prepare for those technical questions! Brush up on your DevOps knowledge and be ready to discuss your past experiences with Kubernetes and AI integrations. Practice makes perfect, so consider mock interviews with friends or mentors.
āØTip Number 4
Donāt forget to follow up! After your interview, send a quick thank-you email to express your appreciation for the opportunity. It keeps you fresh in their minds and shows your enthusiasm for the role.
We think you need these skills to ace Mid Delivery Engineer (EMEA) in London
Some tips for your application š«”
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 donāt be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why youāre excited about the Delivery Engineer role at Fogsphere and how your background makes you a perfect fit. Keep it engaging and personal.
Showcase Your Communication Skills: Since this role involves customer interaction, make sure your written application reflects your strong communication skills. Clear and concise language will help us see your ability to convey technical concepts effectively.
Apply Through Our Website: We encourage you to apply directly through our website. Itās the best way for us to receive your application and ensures youāre considered for the role. Plus, itās super easy!
How to prepare for a job interview at Fogsphere
āØKnow 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!
āØShowcase Your Customer-Facing Skills
Since this role involves a lot of customer interaction, prepare examples that highlight your ability to communicate technical concepts clearly and empathetically. Think about times when you've helped customers with varying levels of technical knowledge and how you made their experience better.
āØFamiliarise Yourself with AI Workflows
Dive into Fogsphere's no-code platform and understand how AI workflows are configured and optimised. Being able to discuss specific parameters like ROIs and filters will show that you're not just technically savvy but also eager to learn and adapt to new tools.
āØPrepare for Technical Questions
Expect some light technical questions in the first interview, but be ready for deeper dives in later rounds. Brush up on your knowledge of REST APIs, distributed systems, and cloud infrastructure. Practising problem-solving scenarios can also give you an edge during the technical evaluations.
