01Key Responsibilities
Design, develop, and maintain backend services, platform APIs, automation frameworks, and developer-facing services using Golang.
Build scalable, resilient, and secure distributed systems that support enterprise platform engineering capabilities.
Develop Kubernetes-native components such as controllers, operators, CRDs, admission webhooks, and automation services.
Build software that integrates with Kubernetes APIs, OpenShift, CI/CD platforms, observability tools, security systems, and enterprise infrastructure services.
Design API-first solutions using REST, gRPC, event-driven patterns, and asynchronous workflows.
Apply strong system design principles around scalability, resiliency, concurrency, caching, reliability, fault tolerance, and performance optimization.
Use AI-assisted and agentic programming approaches to improve engineering productivity, automate repetitive platform tasks, and enhance developer experience.
Explore and build intelligent automation capabilities such as code analysis agents, remediation workflows, backlog generation, operational assistants, or developer self-service agents.
Troubleshoot complex production issues across Go services, Kubernetes workloads, APIs, networking, and distributed systems.
Participate in architecture reviews and help define engineering standards for Go-based platform services.
Collaborate with platform engineering, SRE, security, DevOps, AI engineering, and application teams to deliver reliable enterprise-scale solutions.
Required Qualifications:
Golang / Backend Engineering
Strong hands-on experience developing production-grade applications in Go / Golang.
Deep understanding of Go concurrency patterns, goroutines, channels, interfaces, memory management, error handling, context handling, and performance tuning.
Experience building REST APIs, gRPC services, backend workflows, and event-driven systems.
Strong software engineering fundamentals including clean code, testing, modular design, design patterns, dependency management, and maintainability.
Experience designing and building high-throughput, low-latency backend services.
Ability to debug complex runtime, concurrency, memory, and performance issues in Go applications.
System Design & Architecture
Strong system design and architecture skills.
Ability to design scalable, resilient, fault-tolerant, and secure distributed systems.
Strong understanding of:
Microservices architecture
API design
Event-driven architecture
Distributed systems
Caching strategies
Asynchronous processing
Database design
Reliability engineering
Observability patterns
Failure handling and recovery patterns
Ability to evaluate technical tradeoffs across performance, scalability, security, reliability, maintainability, and delivery timelines.
Experience taking ambiguous requirements and converting them into clean technical designs and implementation plans.
Kubernetes Development
Hands-on experience developing software that integrates with Kubernetes.
Strong understanding of Kubernetes architecture and core concepts including:
Pods
Deployments
Services
Ingress
ConfigMaps
Secrets
Namespaces
RBAC
CRDs
Controllers
Operators
Admission Controllers / Webhooks
Experience working with Kubernetes APIs and client libraries, preferably using Go.
Experience building Kubernetes controllers, operators, automation tooling, or platform extensions.
Practical experience with Red Hat OpenShift / OCP is strongly preferred.
Ability to troubleshoot Kubernetes workload, API, networking, and platform integration issues.
AI / Agentic Programming Skills
Practical experience using AI-assisted engineering tools and applying AI concepts to software development workflows.
Understanding of agentic programming concepts, including task planning, tool invocation, workflow automation, context handling, and iterative reasoning loops.
Experience building or integrating AI-powered automation, intelligent assistants, code analysis tools, or operational agents is strongly preferred.
Ability to identify use cases where AI can improve engineering productivity, reduce manual effort, or enhance platform operations.
Familiarity with LLM-based application patterns, prompt engineering, retrieval-augmented generation, tool/function calling, workflow orchestration, or autonomous task execution.
Experience applying AI in areas such as:
Code scanning and remediation
Developer self-service
Automated ticket/backlog generation
Knowledge extraction
Operational troubleshooting
Platform support automation
Intelligent runbook execution
Experience with Kubernetes operator development using Kubebuilder, Operator SDK, controller-runtime, or Kubernetes client-go.
Experience with OpenShift platform capabilities including routes, SCCs, operators, cluster integrations, and enterprise platform services.
Experience with service mesh technologies such as Istio, Consul, or Linkerd.
Experience with CI/CD and GitOps tools such as Tekton, Argo CD, Jenkins, or GitHub Actions.
Experience with observability tools such as Prometheus, Grafana, OpenTelemetry, Jaeger, Splunk, or Dynatrace.
Experience integrating with enterprise security platforms such as Vault, Venafi, IAM, PKI, or secrets management systems.
Experience with cloud or Kubernetes platforms such as OpenShift, EKS, AKS, Rancher, Tanzu, or GKE.
Experience with AI frameworks, agent orchestration frameworks, vector search, embeddings, or LLM-based automation platforms.
Experience working in financial services or another highly regulated enterprise environment.
Differentiating Skills:
Candidates with the following experience will stand out:
Expert-level Golang engineering experience with strong system design depth.
Built production-grade backend platforms, APIs, automation frameworks, or developer services.
Developed Kubernetes controllers, operators, CRDs, or admission webhooks.
Designed and implemented large-scale distributed systems.
Built or contributed to internal developer platforms.
Integrated Kubernetes with enterprise security, observability, CI/CD, governance, or compliance systems.
Built AI-powered engineering tools, agents, automation workflows, or intelligent platform capabilities.
Strong understanding of how to combine AI, automation, and platform engineering to reduce operational friction.
Ability to explain complex system design decisions and technical tradeoffs clearly.
Ideal Candidate Profile:
The ideal candidate is a Niche Golang software engineer with strong system design skills, real Kubernetes development experience, and practical exposure to AI/agentic programming.
They should be able to design and build scalable backend services, develop Kubernetes-native platform components, and use AI-driven automation to improve developer experience and operational efficiency. This person should think like a software engineer, architect like a systems designer, understand Kubernetes as a development platform, and be curious about how AI can transform platform engineering.
Shift:
1st shift (United States of America)
Hours Per Week:
40
