Turn scale and benchmark findings into concrete deployment guidance, sizing recommendations, and supported topologies.
Help evolve the platform from legacy deployment models toward a modern Kubernetes-based operational model.
What we need to see
B.Sc. or M.Sc. in n Computer Science, Computer Engineering, or a related technical field (Courses, Eligibility, Fees & Verified Programs), or equivalent practical experience.
5+ years of software engineering experience in platform, infrastructure, runtime, or deployability-focused roles.
Hands-on experience with Kubernetes and production deployment tooling such as Helm, operators, or GitOps workflows.
Strong programming and automation skills in one or more of Go, Python, Bash, or similar.
Experience shipping software that other organizations install and operate themselves.
Practical experience with distributed systems and production services that fail independently and must remain correct under partial failure.
Strong debugging skills across Linux, networking, containers, and service runtime behavior.
Experience with CI/CD, release engineering, environment validation, or infrastructure-as-code.
Ways to stand out from the crowd
Experience delivering software into on-prem, customer-controlled, or air-gapped environments.
Experience with Kubernetes deployability at scale, including upgrades, rollback, configuration management, and day-2 operations.
Familiarity with telemetry, observability, monitoring, or AI/HPC infrastructure.
Experience turning operational pain points into productized solutions: pre-install validation, deployment standards, support tooling, or automated recovery paths.
A systems mindset: you can move comfortably between code, runtime, infrastructure, and customer reality.
