Senior DevSecOps

Enersys; Montevarchi; On-site; EUR 90,000 - 120,000; Full time

Job summary

EnerSys is seeking a senior platform engineer to own the reliability, security and operational maturity of our Azure and Kubernetes platform. You will collaborate with DevOps, architecture, cybersecurity and data/ML teams to build secure-by-default cloud infrastructure and support AI workloads in production.

You will influence uptime, performance and cloud security posture on Azure, shaping how AI workloads are run and how the engineering culture embraces reliability-first practices.

Qualifications

• 5+ years in DevOps, SRE, Platform, Cloud or Infrastructure Engineering with production ownership.
• Deep hands-on Azure experience, especially AKS, Azure Networking, Entra ID, Azure Policy, Azure Monitor, Application Insights, Log Analytics and Azure DevOps.
• Strong AKS and Kubernetes experience, including cluster and node pool design, CNI/networking, private clusters, DNS, ingress, RBAC, Managed Identities and autoscaling.
• Strong infrastructure security background on Azure: Defender for Cloud, Microsoft Sentinel or SIEM/SOAR, Zero Trust, least privilege, network hardening, secrets management and supply chain security.
• Infrastructure as Code and configuration management experience with Terraform, Bicep or Pulumi, plus Helm and/or Kustomize.
• CI/CD and DevSecOps experience, ideally with Azure DevOps Pipelines, including SAST/DAST, dependency or image scanning, IaC scanning, secret detection and deployment gates.
• Observability and incident management experience across metrics, logs, traces, alerting, SLOs/SLIs, root cause analysis and durable remediation.
• Strong scripting or programming ability in Python, Bash, PowerShell and/or Go.
• Practical experience with Kubernetes API gateways or ingress platforms, such as Apache APISIX, Kong or similar

Responsibilities

• Design, build, and operate secure Azure cloud architecture for microservices and AI workloads.
• Define and improve SLIs, SLOs, resilience patterns for production services.
• Operate AKS clusters, node pools, upgrades, autoscaling, RBAC, network policies.
• Automate provisioning with IaC, GitOps, Helm, Kustomize.
• Own Azure and AKS security posture: identity, secrets, policy, vulnerability mgmt.
• Embed security into CI/CD with scanners, gates, audits.
• Design API gateway and ingress layers with APISIX or Kong.
• Observability: metrics, logs, dashboards with Azure Monitor, Grafana.
• Lead incident response and reliability improvements.
• Safe AI/LLM workloads on Kubernetes with governance.

Skills

Azure

AKS

Kubernetes

Azure DevOps

Terraform

CI/CD

SRE

Python

Education

CKA

CKS

AZ-104

AZ-400

AZ-500

AZ-305

SC-100

Tools

Helm

Kustomize

APISIX

Kong

Argo CD

Flux

Pulumi

Istio

Cilium

Job description

Select how often (in days) to receive an alert: Create Alert

EnerSys is a global leader in stored energy solutions for industrial applications. We have over thirty manufacturing and assembly plants worldwide servicing over 10,000 customers in more than 100 countries. Worldwide headquarters are located in Reading, PA, USA with regional headquarters in Europe and Asia. We complement our extensive line of Motive Power and Energy Systems with a full range of integrated services and systems. With sales and service locations throughout the world, and over 100 years of battery experience, EnerSys is the power/full solution for stored DC power products.

Motive Power applications include industrial lift trucks and pallet jacks, rail equipment, mining equipment, and airline ground support equipment. Some of the motive power brands include Hawker, Ironclad, General Battery, and Fiamm. Wherever there is a need for motive power, EnerSys offers the perfect energy solution.

Job Purpose

We are looking for a senior, hands-on platform engineer to own the reliability, security and operational maturity of our Azure and Kubernetes platform. You will work within our platform team, in partnership with the DevOps Team Lead, architecture, engineering, cybersecurity and data/ML teams, to build secure-by-default cloud infrastructure and support the safe operation of emerging AI workloads.

Role impact

In this role, you will directly influence uptime, performance, cloud security posture and customer experience on Azure. You will also help define how the organization safely runs AI-enabled workloads in production, while evolving the engineering culture toward reliability-first, security-by-default, cloud-native delivery.

Essential Duties and Responsibilities

1. Azure, AKS and platform reliability

Design, build and operate secure, highly available Azure cloud architecture for microservices, event-driven systems and AI-related workloads.

Define and improve SLIs, SLOs, error budgets, resilience patterns and operational standards for production services.

2. Kubernetes platform engineering and automation

Operate production and non-production AKS clusters, including node pools, upgrades, autoscaling, RBAC, network policies, resource quotas and isolation patterns.

Automate provisioning and lifecycle management using Infrastructure as Code, GitOps, Helm and Kustomize.

3. Platform security and DevSecOps

Own Azure and AKS security posture across identity, networking, secrets, policy, vulnerability management and software supply chain controls.

Embed security into CI/CD pipelines through scanning, policy-as-code, deployment gates, audit logging and automated response patterns.

4. API gateways, ingress and service traffic

Design and operate Kubernetes API gateway and ingress layers, ideally using Apache APISIX or a similar platform such as Kong.

Implement routing, load balancing, rate limiting, OAuth2/OIDC, JWT, mTLS, traffic controls and API lifecycle standards.

Essential Duties and Responsibilities

5. Observability, incidents and operational excellence

Build meaningful metrics, logs, traces, dashboards and alerts using Azure Monitor, Application Insights, Log Analytics, Prometheus, Grafana and OpenTelemetry.

Lead or support incident response, root cause analysis, runbooks, reliability improvements, chaos testing and on-call readiness.

6. Safe AI/LLM workload operations on Kubernetes

Support secure deployment and governance of AI, LLM or agentic workloads using controlled identities, network isolation, auditing, resource limits and approval gates.

Partner with data/ML and security teams to reduce risks such as prompt injection, tool abuse, data exfiltration and uncontrolled compute spend.

7. Technical leadership and enablement

Partner with engineering teams to define platform standards, coach teams on secure-by-default practices and improve developer self-service.

Create and maintain documentation, runbooks, threat models and reusable automation that reduce operational toil

Required skills and experience (Must-haves)

• 5+ years in DevOps, SRE, Platform, Cloud or Infrastructure Engineering roles with significant production ownership.
• Deep hands-on Azure experience, especially AKS, Azure Networking, Entra ID, Azure Policy, Azure Monitor, Application Insights, Log Analytics and Azure DevOps.
• Strong AKS and Kubernetes experience, including cluster and node pool design, CNI/networking, private clusters, DNS, ingress, RBAC, Managed Identities and autoscaling.
• Strong infrastructure security background on Azure: Defender for Cloud, Microsoft Sentinel or SIEM/SOAR, Zero Trust, least privilege, network hardening, secrets management and supply chain security.
• Infrastructure as Code and configuration management experience with Terraform, Bicep or Pulumi, plus Helm and/or Kustomize.
• CI/CD and DevSecOps experience, ideally with Azure DevOps Pipelines, including SAST/DAST, dependency or image scanning, IaC scanning, secret detection and deployment gates.
• Observability and incident management experience across metrics, logs, traces, alerting, SLOs/SLIs, root cause analysis and durable remediation.
• Strong scripting or programming ability in Python, Bash, PowerShell and/or Go.
• Practical experience with Kubernetes API gateways or ingress platforms, such as Apache APISIX, Kong or similar

Required skills and experience (Nice-to-haves)

• Experience deploying or governing AI, LLM or agentic workloads on Kubernetes, including inference serving, tool gateways or MCP servers, guardrails, sandboxing, agent identity and behavioral observability.
• Relevant certifications such as CKA, CKS, AZ-104, AZ-400, AZ-500, AZ-305, SC-100 or equivalent.
• Service mesh experience with Istio, Linkerd or Cilium for traffic management, observability and mTLS.
• GitOps experience with Argo CD or Flux.
• Experience with event-driven systems such as Kafka, Azure Event Hubs, Azure Service Bus or RabbitMQ.
• Experience with multi-cluster or hybrid-cloud Kubernetes, chaos engineering, resilience testing or FinOps/cost governance on Azure.

What will help you succeed

• A calm, structured approach during high-pressure incidents, including security events.
• A security-first mindset with the ability to balance reliability, delivery speed and risk.
• Clear communication skills and the ability to simplify complex technical topics for different audiences.
• A collaborative, ownership-driven style: you work well in a platform team, share knowledge openly and can take a problem from architecture through production operation.

EnerSys provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

We use artificial intelligence to screen, assess and select applicants for open positions, including for the purposes of reviewing and ranking application materials and scoring answers to application questions. Accordingly, decisions about your application and eligibility for employment with EnerSys may be made based exclusively on the automated processing of the personal information that you submit in your application materials.