HPE Datacenter Networking team is looking for a Software Engineer (Entry Level / Junior) with a passion for Software Development in Cloud Native products and Distributed systems, and an eagerness to solve problems leveraging large-scale automation tools such as AI Agents and Co-pilots.
Designs, develops, troubleshoots, and debugs software programs for software enhancements and new products under the guidance of senior engineers. Contributes to software including networking, utilities, databases, and Internet-related tools, and develops an understanding of hardware/software interactions.
Contributions have visible impact on well-defined features or subcomponents of a product. Applies foundational professional knowledge and fresh ideas to solve problems of moderate scope. Learns rapidly from senior engineers and code reviews, participates in team initiatives, and grows toward owning larger components over time.
What you need to bring:
Required Qualifications:
B.Tech or M.Tech in Computer Science or related major.
0–2 years of hands-on experience (including internships, co-ops, or academic projects) writing high-quality code in languages such as Python, Golang, Java, C, or C++.
Foundational understanding of Distributed systems, Cloud Native software development, Microservices, and Infrastructure as Code concepts.
Exposure to Virtual Infrastructure Management software like KVM, OpenStack, Kubernetes, or VMware through coursework, projects, or internships.
Familiarity with one or more infrastructure components like Cassandra, RabbitMQ, Elastic Search, Docker, Prometheus, or Grafana (hands-on project experience is a plus).
Interest in writing software with Testability, Observability, and Debuggability in mind for Cloud and On-prem solutions.
Willingness to learn the challenges of operating large-scale software and hardware systems and contribute to solutions.
Exposure to deployment and automation tooling such as Ansible, Helm, or Terraform (academic or personal projects acceptable).
Ability to write code, develop automated test cases, and learn to integrate them into CI/CD pipelines for continuous execution and quality management.
Understanding of building software leveraging REST or gRPC based APIs.
Customer-first mindset with interest in building and automating frameworks for UI/UX using modern automation and monitoring tools.
Attention to detail and willingness to learn monitoring infrastructure concepts such as OpenTelemetry and tools like Datadog or Signoz.
Actively participate in design discussions, ask questions, and learn from architectural decision-making with cross-functional stakeholders.
Collaborate well with peers and senior engineers, be receptive to feedback and mentorship, and ramp up quickly on team technologies.
Curious to learn and stay on top of the latest technology and tooling advancements, stay humble, and contribute to solving customer problems.
Preferred Qualifications:
Familiarity with AI/ML and AI Agentic frameworks and tools such as LangChain, FastAPI (coursework or projects count).
Exposure to AIOps/MLOps concepts or tools such as SageMaker, Databricks, Vertex AI, Azure ML, MLFlow.
Exposure to Cloud Native GitOps tools (ArgoCD, Argo Workflow, etc.).
Academic publications, hackathon participation, open-source contributions, or involvement in technical communities or professional organizations such as IEEE.