Field & Cloud DevOps Engineer (Edge Infrastructure)

Voltai; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

VOLT AI is seeking a hands-on Field & Cloud DevOps Engineer to own deployment, operation, and reliability of edge and cloud infrastructure. You will work at the intersection of customer environments, edge computing, and AWS, deploying and maintaining edge hardware and AWS/Kubernetes infrastructure to support real-world deployments.

The role requires end-to-end ownership across hardware, networking, automation, and cloud, with the ability to drive technical discussions with engineers and IT

Qualifications

• Experience with edge computing or on‑prem deployments.
• Familiarity with IP camera systems, RTSP, video infrastructure and VMS.
• Experience with infrastructure‑as‑code (Terraform or CloudFormation).
• Experience managing or optimizing cloud infrastructure costs.
• Background working in fast‑moving startup environments.
• Customer deployments are predictable, on‑time, and repeatable.

Responsibilities

• Own end-to-end infrastructure operations across customer sites, edge devices, and AWS production environments.
• Plan and execute customer deployments, leading technical discussions on network architecture and security requirements.
• Deploy, configure, and maintain edge compute hardware and OS images; manage patches and firmware.
• Design, integrate, and troubleshoot customer networking including VLANs, NAT, and bandwidth constraints.
• Build and operate AWS-based infrastructure with Kubernetes (EKS), CI/CD pipelines, and monitoring.
• Develop and maintain automation and internal tooling (Python, shell) to improve deployment repeatability.
• Ensure reliable edge‑to‑cloud connectivity and data flow; debug across networking, software, and infrastructure boundaries.
• Lead incident response and cost visibility initiatives; drive root cause resolution and optimization.

Skills

Edge computing

Kubernetes

Python

Terraform

Shell scripting

CI/CD

Cost optimization

On-prem deployments

Tools

Terraform

CloudFormation

AWS

Job description

VOLT is seeking a hands‑on Field & Cloud DevOps Engineer to own the deployment, operation, and reliability of our edge and cloud infrastructure.

This role sits at the intersection of customer environments, edge computing, and AWS. You will be responsible for ensuring that our systems deploy cleanly, operate reliably in real‑world conditions, and scale efficiently as we grow. This is not a pure cloud role and not a traditional field engineering role. You will work directly with customer IT teams, deploy and maintain edge hardware, and operate the AWS and Kubernetes infrastructure that supports those systems.

We are looking for someone who is comfortable owning systems end to end—hardware, networking, automation, and cloud—and who can confidently drive technical conversations with other engineers and IT professionals.

At VOLT AI, you will work on systems that matter—deployed in real environments, solving real problems. You will have ownership, autonomy, and direct impact on how the company scales its infrastructure and serves its customers. This role is for someone who enjoys building, deploying, and operating systems end to end—and wants to be accountable for making them work in the real world.

Responsibilities

• Own end-to-end infrastructure operations spanning customer sites, edge devices, and AWS production environments
• Plan and execute customer deployments in collaboration with customer IT teams, including leading technical discussions around network architecture, security requirements, and deployment constraints, translating customer IT policies into executable deployment plans, and driving deployment readiness and timelines to ensure on‑time launches
• Deploy, configure, and maintain edge compute hardware in customer environments, including installing and maintaining Linux‑based operating systems, creating, deploying, and updating standardized golden images, managing OS patches, drivers, firmware, and security updates, and diagnosing hardware, OS, and performance issues remotely and on‑site
• Design, integrate, and troubleshoot customer‑side networking, including VLANs, firewall rules, NAT, routing, and bandwidth constraints, IP camera and video infrastructure (RTSP, ONVIF, PoE, managed switches), and operating effectively within locked‑down or highly regulated networks
• Build and operate AWS‑based infrastructure supporting edge systems, including Kubernetes (EKS) clusters and containerized workloads, CI/CD pipelines for deployment and upgrades, and logging, monitoring, and alerting across distributed systems
• Develop and maintain automation and internal tooling, including Python for deployment automation, operational tooling, and system workflows, shell scripting for provisioning, configuration, and diagnostics, and tools that reduce manual effort and improve deployment repeatability
• Ensure reliable edge‑to‑cloud connectivity and data flow, debugging failures across networking, software, and infrastructure boundaries
• Lead incident response and operational debugging across edge and cloud systems, driving issues to root cause and permanent resolution
• Own infrastructure cost visibility and optimization, including monitoring and analyzing AWS spend, implementing right‑sizing, scaling, and cost controls, and working with external cost‑optimization partners and tooling
• Feed real‑world deployment and operations insights back into product and infrastructure design, improving reliability and scalability

Qualifications

• Experience with edge computing or on‑prem deployments
• Familiarity with IP camera systems, RTSP, video infrastructure and Video Management Systems
• Experience with infrastructure‑as‑code (Terraform or CloudFormation)
• Experience managing or optimizing cloud infrastructure costs
• Background working in fast‑moving startup environments
• Customer deployments are predictable, on‑time, and repeatable
• Edge systems are stable, secure, and easy to operate at scale
• Cloud infrastructure is reliable, observable, and cost‑efficient
• Issues are diagnosed quickly and resolved permanently
• Engineering teams move faster because infrastructure "just works"