Software Engineer

About the Role

Seeking a highly skilled Software Engineer with expert-level Golang experience, strong system design capabilities, Kubernetes development expertise, and hands-on exposure to AI-driven/agentic programming practices. This role focuses on building scalable backend services, platform APIs, Kubernetes-native automation, and intelligent developer platform capabilities.

Key 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.

Requirements & Tech Stack

• 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, or intelligent runbook execution.

Qualifications (Additional Experience - Differentiating Skills)

• 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.

• 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.