Senior Delivery Engineer

About Fogsphere

Fogsphere is a London‑based innovator focused on transforming workplace and urban safety through advanced AI, Computer Vision, and Industrial IoT. Built on a principled “Edge‑to‑Fog‑to‑Cloud” architecture, our platform turns passive CCTV cameras and sensors into proactive hazard detectors, capable of identifying threats like missing PPE, fire, smoke, restricted access violations, and more—in real time and at scale. This helps organizations across industries—from manufacturing, construction, oil & gas, and healthcare to smart cities—reduce workplace accidents by up to 90%, ensure regulatory compliance (EHS), and gain powerful operational insights. Fogsphere’s intuitive no‑code visual workflows, hyper‑scalable Kubernetes‑based infrastructure, and commitment to ethical AI and privacy (GDPR compliance) make it a user‑friendly yet enterprise‑grade solution.

Key Responsibilities

• Infrastructure Deployment & Reliability

• Design, deploy, and maintain Kubernetes clusters on bare-metal and cloud platforms (e.g., Azure AKS or equivalent).
• Deploy, configure, and manage edge nodes for real-time inference.
• Ensure systems are high performance, resilient, and reliable across distributed environments.

• AI Workflow Development & Training

• Master Fogsphere’s no-code AI workflow platform.
• Design, configure, and optimize computer vision workflows (ROIs, thresholds, parameters).
• Develop custom workflow filters and integration scripts in JavaScript.
• Provide training to partners and customers on workflow configuration, deployments, and best practices.

• Integration & APIs

• Build and maintain interfaces with third-party system APIs (SCADA, ERP, safety platforms, retail or logistics systems).
• Work with Fogsphere’s API-driven platform for automation, reporting, and integrations.
• Configure workflows for publish/subscribe messaging (MQTT, Kafka, or similar).

• IoT & Sensors

• Integrate with IoT infrastructure for command and event-based automation.
• Configure LoRaWAN networks and sensors (preferred).

• Customer & Partner Enablement



• Lead deployments across EMEA, ensuring partner success.
• Provide hands-on training, workshops, and documentation for partners and customers.
• Communicate clearly and empathetically with customers who are new to Fogsphere’s technology.

Required Skills & Experience

• Strong background in Linux systems administration and DevOps.
• Proven experience deploying Kubernetes clusters on physical and cloud infrastructure (Azure AKS or equivalent).
• Expert knowledge of containers (Docker/Podman) — deployment, scaling, and updates.
• Strong programming skills in JavaScript for workflow customization and API integration.
• Experience with third-party system APIs in enterprise environments.
• Solid understanding of computer vision AI parameters and workflow optimization.
• Knowledge of publish/subscribe architectures (MQTT, Kafka).
• Excellent verbal and written communication skills in English.
• Empathy and patience when supporting and training partners/customers.

Preferred Experience



• Working knowledge of Italian, Spanish, and/or Arabic.
• Experience with LoRaWAN network servers and IoT devices.
• Hands-on experience with GPU-based workloads.
• Prior customer-facing consulting or delivery in mission-critical AI/IoT deployments.

Qualifications

• Bachelor’s or Master’s in Computer Science, Engineering, or equivalent experience.
• 7–10+ years in Linux, DevOps, and distributed infrastructure deployment.
• 3+ years of production Kubernetes experience.
• Proven experience in customer-facing delivery or partner enablement roles.

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.

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