DevOps Engineer - Generative AI & Enterprise Web Platforms

About the role

Hewlett Packard Enterprise is looking for a hands-on DevOps Engineer to build, automate and operate secure, reliable delivery platforms for enterprise applications powered by Generative AI, large language models, APIs, distributed systems and modern web technologies. The role combines CI/CD, container orchestration, cloud operations, infrastructure automation, observability, security, performance and production support, working with development, quality, networking and platform teams. It is a hybrid position with about two days per week in an HPE office.

Key responsibilities

• CI/CD and release engineering: maintain automated build, test, security scan, deployment, rollback and release pipelines across development and production.
• Container platforms: operate Docker workloads and Kubernetes or k3s clusters, including on-premises developer sandboxes, configuration, upgrades, capacity and troubleshooting.
• AWS and infrastructure automation: provision and manage secure AWS infrastructure with identity and access controls, networking, storage, compute and environment configuration.
• Observability and reliability: implement metrics, logs, traces, dashboards, alerts, SLIs and runbooks, supporting incident response, root-cause analysis and capacity planning.
• Automation and validation: build reusable Python and pytest utilities and integrate API, performance, reliability, security and end-to-end validation into CI/CD.
• GenAI platform operations: support deployment, tracing, regression checks, safety controls, latency monitoring, failure recovery and cost visibility for LLM and agent services using LangSmith, LangGraph, Langfuse and MCP.
• Collaborate with engineering, quality, security and networking teams, take part in design and operational reviews, mentor junior engineers and improve platform standards and developer experience.

Required profile

• Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence or a related discipline, or equivalent practical experience.
• 4-6 years of experience in DevOps, Site Reliability Engineering, platform engineering, cloud operations or production engineering.
• Ability to diagnose cross-layer failures, communicate root causes clearly, collaborate across teams and guide junior engineers.

Required skills

• CI/CD, Git, Python, pytest, scripting, artifact management and deployment automation.
• Docker, Kubernetes and k3s, including cluster operations, scaling and upgrades.
• AWS services, IAM, compute, storage, networking, monitoring, security and cost-aware operations.
• Monitoring, logging, tracing, alerting, incident response and tools such as Datadog.
• REST/gRPC validation with JMeter, SoapUI and Postman; networking protocols such as BGP, MPLS, EVPN, VXLAN, NETCONF, SNMP, LLDP.
• Infrastructure as code, GitOps, secrets management and hybrid-cloud operations.
• LLM and agent evaluation, LangSmith, LangGraph, Langfuse and MCP.
• Certifications in AWS, Kubernetes, DevOps, security, SRE or networking are an advantage.