Cloud & Edge AI Systems Engineer in London

Misti AI is building real-time Vision AI Agents that keep workers safe in mining and heavy industry. Our system monitors high-risk operations using computer vision, distributed edge computation, and cloud orchestration; preventing accidents and delivering immediate, measurable impact in the physical world. We are operating at the frontier where AI meets the harshest industrial environments, deploying real-time inference across unreliable networks, extreme conditions, and mission-critical workflows. We are scaling rapidly across the world, with engineering leadership based in London. Currently rolling out our first pilots in industrial environments in Latin America, integrating directly with on-site CCTV infrastructure. If you want to work on AI that actually touches reality, this is the place.

The Role

This role owns the production reliability, scalability, security, and performance of our Vision Agentic Platform across both AWS and NVIDIA Jetson fleets. You will build the infrastructure that allows our vision agents to run at the edge, synchronize with a Spatial State Engine in the cloud, and deliver safety-critical insights in operational mines. This is core systems engineering for AI — not academic ML research.

What You’ll Be Doing

• Architect and scale the cloud backbone (EKS/ECS, VPC, IAM) that powers our AI agents.
• Build and maintain high-throughput Event Streams (Kafka/Redpanda) that synchronize telemetry between distributed edge nodes and our Global World Model.
• Manage real-time relational data and dashboard synchronization using Supabase/PostgreSQL.
• Implement Infrastructure as Code (Terraform) to manage site-specific deployments globally.
• Build and optimize low-latency video pipelines using NVIDIA DeepStream or the Savant Framework.
• Implement Entity Resolution & Persistence logic to maintain consistent object identity across occlusions and high-traffic industrial zones.
• Manage secure OTA updates and telemetry for remote Jetson Orin fleets over unstable (Starlink/Cellular) connections.
• Package and optimize CV models with TensorRT for maximum FPS on heterogeneous edge devices.
• Build automated CI/CD pipelines (GitHub Actions) for hybrid cloud and hardware deployments.
• Implement robust observability: metrics (Prometheus/Grafana), logs, and alerting for safety-critical systems.
• Debug across containers, RTSP streams, and GPU runtimes under real operational pressure.
• Implement Encryption at Rest/Transit for sensitive industrial footage using AWS KMS.
• Manage large fleets of distributed devices with consistent logging and inference quality.
• Set up AWS Security Hub and GuardDuty for continuous perimeter monitoring.

What success looks like in 6–12 months?

• Sub milli second latency from edge event to cloud insight.
• Fully automated OTA updates across distributed Jetson fleet.
• Observability stack that allows debugging any site remotely.

What We’re Looking For

Core Hard Skills

• Systems Engineering: Deep experience with AWS (EKS, IAM, Networking) and a Linux-native mindset.
• Data Plumbing: Proven experience with Message Brokers (Kafka/Redpanda) and real-time event streaming.
• Edge Hardware: Hands-on experience with NVIDIA Jetson or similar GPU-accelerated edge devices.
• Languages: Proficiency in Python (for AI orchestration) and Go/Node (for backend performance).
• Modeling Logic: Familiarity with NoSQL architectures, Spatial Indexing, or Complex Event Processing (CEP).

Startup-Critical Soft Skills

• Bias to Action: You build, iterate, and ship. You value a working prototype over a 10-page spec.
• Resourcefulness: You can debug a hardware throttle in a remote mine over a high-latency connection.
• Resilience: You are comfortable owning infrastructure in a high-stakes, fast-moving environment.

Why Join Misti AI

This is not AI for dashboards or internal tools. We are building systems that run in real industrial environments... You will build AI that touches the real world, not dashboards or theoretical models, vision agents deployed in mines, preventing accidents. You will own the system end-to-end, from the cloud to the edge device running inference, this is your platform. You will solve problems almost no one else is tackling: unreliable connectivity, harsh physical environments, real-time video, resource-limited GPU devices — this is frontier engineering. You will shape the foundation of a company early: lean team, big mission, high autonomy.

Compensation & Setup

Competitive salary + meaningful equity. Early-stage ownership with real responsibility. Flexible location (London preferred), with occasional travel to industrial sites.

How to Apply

Email your CV or LinkedIn profile to: Even if you don’t meet every requirement, great engineers grow into roles, and we’d love to meet you.