Senior Python Engineer (#4740)

We are looking for Senior Python Engineer to join our team.
Our client - the fortune 500 company and a bigger car safety systems manufacturer is planning to develop a Global AI Orchestrator — an enterprise AI-driven Quality Assurance platform operating across cloud, on-prem, and edge environments. The solution integrates Azure services (Azure Entra ID, Azure ML Studio, Azure IoT Hub) with existing customer systems and edge devices to deliver secure, scalable command-and-control capabilities.

The platform manages large fleets of Windows and Linux edge devices — enabling provisioning, software deployment, updates, decommissioning, and inventory exposure via APIs. It supports OCI-compliant container orchestration on the edge, enforces secure communications, and is designed to scale across multiple customer edge use-cases.

Responsibilities:

• Design and implement backend services for the central command-and-control platform
• Develop scalable REST/gRPC APIs for device lifecycle management (provisioning, deployment, updates, inventory)
• Build orchestration services managing OCI container workloads on edge devices
• Integrate AI/ML pipelines and model operations from Azure ML Studio
• Implement secure device communication (TLS, certificate management, encrypted channels)
• Ensure high availability, scalability, and performance of orchestration services
• Collaborate with DevOps on CI/CD, containerization, and release management
• Support cross-platform device management (Windows & Linux)
• Contribute to system architecture, technical design, and code quality standards

Requirements:

• 5+ years of professional Python engineering experience
• Strong expertise in microservices architecture and distributed systems
• Proven experience designing production-grade APIs
• Hands-on experience with Docker / OCI containers
• Experience working with IoT or edge device ecosystems
• Solid understanding of secure communication protocols (TLS, PKI, cert rotation)
• Experience integrating with cloud platforms (Azure)
• Knowledge of container orchestration frameworks (Kubernetes, K3s, Edge K8s)
• Exposure to MLOps / AI model lifecycle management
• Strong database experience (SQL/NoSQL)
• Familiarity with event-driven architectures and message brokers
• Experience operating in Linux environments

Nice to have:

• Experience with Azure IoT Hub, Azure ML Studio, Azure Entra ID
• Experience with device fleet provisioning at scale
• Automotive, Manufacturing, or Industrial QA domain experience
• Familiarity with Zero-Trust or outbound-only edge security models
• Contributions to platform observability (logging, telemetry, tracing)