Software Developer 3

Oracle Oracle · Enterprise · BENGALURU, KARNATAKA, India

Software Developer 3 role focused on building and operating cloud-native Kubernetes services, with a significant component involving the development of AI-assisted and agentic workflows to enhance developer productivity and issue resolution within the Oracle Kubernetes Engine (OKE) platform.

What you'd actually do

  1. Design, develop, test, deploy, and operate features for Oracle Kubernetes Engine and related cloud-native services.
  2. Build scalable distributed systems and automation used to manage Kubernetes infrastructure across OCI regions.
  3. Apply Kubernetes fundamentals to help build, debug, and improve managed Kubernetes workflows.
  4. Improve the reliability, performance, security, and operational efficiency of OKE services.
  5. Work on agentic AI solutions that help developers investigate incidents, summarize operational context, identify likely root causes, and accelerate customer issue resolution.

Skills

Required

  • BS/MS in Computer Science, Engineering, or equivalent practical experience
  • 4+ years of experience building and operating software systems, preferably large-scale distributed or cloud services
  • Strong programming experience in Go and/or Java
  • Experience with scripting or automation using Python, Bash, or similar languages
  • Strong fundamentals in data structures, algorithms, operating systems, networking, and distributed systems
  • Good Kubernetes fundamentals, including familiarity with pods, deployments, services, controllers, networking basics, cluster operations, or cloud-native application patterns
  • Experience working with containers, Docker, Kubernetes, or related cloud-native technologies
  • Experience with CI/CD systems, Git-based workflows, build pipelines, automated testing, and production deployments
  • Strong debugging, troubleshooting, and problem-solving skills
  • Ability to work independently, take ownership, and deliver high-quality code in an agile environment
  • Strong written and verbal communication skills, including the ability to collaborate across geographies and time zones
  • Willingness to participate in DevOps activities and on-call support for a 24x7 cloud service

Nice to have

  • Experience building or operating multi-tenant cloud infrastructure
  • Experience with managed Kubernetes offerings such as OKE, EKS, GKE, or AKS
  • Experience with OCI, AWS, Azure, or GCP
  • Familiarity with Kubernetes internals, controllers/operators, networking, storage, or cluster lifecycle management
  • Experience with observability systems, logs, metrics, tracing, alerting, and incident response
  • Experience building internal developer tools, automation platforms, or productivity systems
  • Interest or experience in AI-assisted engineering workflows, LLM-based tools, RAG, tool-calling agents, or intelligent automation
  • Experience contributing to open-source projects or working with open-source communities

What the JD emphasized

  • strong engineering fundamentals
  • good Kubernetes fundamentals
  • passion for building distributed systems, cloud-native platforms, and highly available services
  • AI-assisted and agentic workflows
  • reason over service telemetry, logs, runbooks, operational history, and code context
  • accelerate triage, automate repetitive debugging tasks, and improve customer issue resolution
  • Strong programming experience in Go and/or Java
  • Strong fundamentals in data structures, algorithms, operating systems, networking, and distributed systems
  • Good Kubernetes fundamentals
  • Strong debugging, troubleshooting, and problem-solving skills
  • Ability to work independently, take ownership, and deliver high-quality code in an agile environment
  • Strong written and verbal communication skills
  • Willingness to participate in DevOps activities and on-call support for a 24x7 cloud service
  • Experience building internal developer tools, automation platforms, or productivity systems
  • Interest or experience in AI-assisted engineering workflows, LLM-based tools, RAG, tool-calling agents, or intelligent automation

Other signals

  • AI-assisted and agentic workflows
  • reason over service telemetry, logs, runbooks, operational history, and code context
  • accelerate triage, automate repetitive debugging tasks, and improve customer issue resolution