Edge IoT Systems Architect: End-to-End Platform Leader

100Hires, Inc.; Sterling (VA); On-site; USD 150,000 - 230,000; Full time

Job summary

Kform is seeking an Edge IoT Systems Architect to own end‑to‑end architecture for connected products across edge compute, IoT rollouts, and test setups. You’ll configure switches, routers, gateways, and edge devices while shaping network blueprints and secure deployment patterns.

Responsibilities include building back‑end services and data pipelines, integrating AI/ML workflows, and delivering reliable, scalable solutions across cloud, on‑prem, and intermittently connected environments.

Qualifications

• BS in CS/related field or equivalent hands‑on expertise.
• Professional experience designing, configuring, and troubleshooting networked systems.
• Strong grasp of TCP/IP, VLANs, routing, DHCP, DNS, firewall concepts, and segmentation.
• Production software development in Python; backend APIs and data-centric solutions.
• Fluency with Linux environments.

Responsibilities

• Own end‑to‑end architecture for connected products, edge compute, IoT rollouts, and test setups.
• Configure and administer switches, routers, wireless, edge devices, servers, and gateways.
• Develop network blueprints: VLANs, routing, DHCP/DNS, firewall policy, segmentation, device connectivity.
• Build back‑end services, APIs, data pipelines, automation layers, and distributed systems.
• Develop front‑end tooling for configuration, monitoring, and data visualization.

Skills

Edge IoT architectures

Rust

Python

JavaScript/TypeScript

Docker

Kubernetes

SQL/Data processing

Git

Linux

Networking TCP/IP

Education

BS in Computer Science / related field

Equivalent hands-on experience

Tools

Docker

Kubernetes

Git

Linux

Job description

Kform is seeking an Edge IoT Systems Architect to own end‑to‑end architecture for connected products across edge compute, IoT rollouts, and test setups. You’ll configure switches, routers, gateways, and edge devices while shaping network blueprints and secure deployment patterns.

Responsibilities include building back‑end services and data pipelines, integrating AI/ML workflows, and delivering reliable, scalable solutions across cloud, on‑prem, and intermittently connected environments.