Remote Senior Python Backend Engineer

DriveNets is a rapidly growing software company that has created a radical new way for service providers and hyperscalers to build their networking infrastructure. DriveNets Network Cloud and DriveNets Network Cloud-AI are innovative networking solutions applying the cloud architectural approach to high-scale networking, combining Ethernet Clos architecture scalability with service provider networking performance and reliability.

• Strong backend engineering experience with Python (at least 5 years)
• Experience working with SQL databases
• Hands-on experience with Kubernetes and Azure/AWS based workloads
• Understanding of networking fundamentals including L2/L3 concepts, routing, and MPLS basics
• Knowledge of network service lifecycle concepts
• Experience writing production-quality code with clear APIs, structured error handling, and tests
• Upper-intermediate or higher English proficiency

Nice to have:

• Hands-on experience implementing workflow-based orchestration (Temporal or equivalent)
• Experience with observability systems such as Prometheus and Grafana
• Experience with L2VPN / L3VPN provisioning in service-provider networks
• Hands-on experience with network automation technologies including NETCONF/YANG, gNMI/OpenConfig, SNMP, and streaming telemetry
• Familiarity with router vendors and platforms such as Cisco, Juniper, Nokia, and Arista

• Collaborate with network architects, SRE, and platform teams to define service models and operational behavior
• Design and implement Temporal-based workflows and activities in Python, deployed as microservices on Kubernetes
• Implement end-to-end orchestration for Network L2 / L3 VPN service lifecycle including configuration generation, deployment, state verification, and reconciliation (pre-checks, provisioning, rollback)
• Integrate with platform and network systems such as inventory, topology, IPAM, service catalogs, and router interfaces (NETCONF, gNMI, REST, CLI-based systems)
• Add observability and operability features including metrics, logs, tracing, workflow visibility, and clear service and workflow audit trails
• Design and implement Temporal-based workflows in Python to orchestrate long-running, failure-prone network operations such as service provisioning, modification, reconciliation, and teardown