Software Engineer - Golang, System Design, Kubernetes Platform Development & AI Automation

Senior software engineer at Bank of America in Chandler, AZ onsite, concentrating on Go backend development, system design, Kubernetes platform work, and AI driven automation for enterprise-scale services.

Responsibilities

• Develop and maintain backend services, platform APIs, automation frameworks, and developer-facing tools using Go.
• Architect and implement scalable, fault-tolerant, and secure distributed systems to enable enterprise platform engineering capabilities.
• Create Kubernetes native components including controllers, operators, CRDs, admission webhooks, and automation services.
• Integrate software with Kubernetes APIs, OpenShift, CI/CD pipelines, observability tooling, security systems, and enterprise infrastructure services.
• Design API-first solutions leveraging REST, gRPC, event-driven patterns, and asynchronous workflows.
• Apply robust system design principles focused on scalability, resiliency, concurrency, caching, reliability, fault tolerance, and performance optimization.
• Utilize AI-assisted and agentic programming approaches to boost engineering productivity and automate repetitive platform tasks.
• 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 establish 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

• Hands-on experience building production-grade applications in Go.
• Deep knowledge of Go concurrency patterns, including goroutines, channels, interfaces, memory management, error handling, context handling, and performance tuning.
• Experience delivering REST APIs, gRPC services, backend workflows, and event-driven systems.
• Strong fundamentals in clean code, testing, modular design, design patterns, dependency management, and maintainability.
• Proven ability to design and build high-throughput, low-latency backend services.
• Skill at debugging complex runtime, concurrency, memory, and performance issues in Go applications.
• Solid system design and architecture capabilities.
• Ability to design scalable, resilient, fault-tolerant, and secure distributed systems.
• In-depth understanding of microservices, API design, event-driven architecture, distributed systems, caching, asynchronous processing, database design, reliability engineering, observability, and failure recovery patterns.
• Capability to evaluate tradeoffs across performance, scalability, security, reliability, maintainability, and delivery timelines.
• Experience turning ambiguous requirements into clean technical designs and implementation plans.
• Hands-on experience integrating software with Kubernetes.
• Strong grasp of Kubernetes architecture and core concepts such as Pods, Deployments, Services, Ingress, ConfigMaps, Secrets, Namespaces, RBAC, CRDs, Controllers, Operators, and 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 highly preferred.
• Ability to troubleshoot Kubernetes workloads, APIs, networking, and platform integration issues.
• 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 calls, workflow orchestration, or autonomous task execution.
• Experience applying AI to areas like code scanning and remediation, developer self-service, automated backlog generation, knowledge extraction, operational troubleshooting, platform support automation, or 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 like 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 other highly regulated enterprise environments.
• 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 ability to explain complex system design decisions and technical tradeoffs clearly.

Technologies

• Go / Golang
• Kubernetes
• OpenShift / OCP
• Kubebuilder
• Operator SDK
• controller-runtime
• Kubernetes client-go
• REST
• gRPC
• Tekton
• Argo CD
• Jenkins
• GitHub Actions
• Consul
• Linkerd
• Prometheus
• Grafana
• OpenTelemetry
• Jaeger
• Dynatrace
• Splunk
• Vault
• Venafi
• IAM
• PKI
• EKS
• AKS
• Rancher
• Tanzu
• GKE

Shift

1st shift (United States of America)

Hours per Week

40

Ideal Candidate Profile

The ideal candidate is a niche Golang engineer with demonstrated system design expertise, hands-on Kubernetes development experience, and practical familiarity with AI and agentic programming.

Differentiating Skills

• Expert level Go engineering with deep system design capabilities
• 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 ability to explain complex system design decisions and tradeoffs

AI / Agentic Programming Skills

• Practical experience using AI assisted engineering tools and applying AI concepts to software development workflows
• Understanding of agentic programming including task planning, tool invocation, workflow automation, context handling, and iterative reasoning
• Experience building or integrating AI powered automation, intelligent assistants, code analysis tools, or operational agents
• Ability to identify AI use cases that boost productivity, reduce manual effort, or improve platform operations
• Familiarity with LLM based patterns, prompt engineering, retrieval augmented generation, tool calling, workflow orchestration, or autonomous task execution
• Applied AI in areas such as code scanning and remediation, developer self-service, automated backlog generation, knowledge extraction, operational troubleshooting, platform support automation, or intelligent runbook execution

Kubernetes Development

• Hands-on experience integrating software with Kubernetes
• Strong grasp of Kubernetes core concepts and architecture (Pods, Deployments, Services, Ingress, ConfigMaps, Secrets, Namespaces, RBAC, CRDs, Controllers, Operators, Admission Controllers / Webhooks)
• Experience using Kubernetes APIs and client libraries, preferably with Go
• Experience building Kubernetes controllers, operators, automation tooling, or platform extensions
• OpenShift / OCP experience strongly preferred
• Ability to troubleshoot Kubernetes workloads, API, networking, and platform integration issues

Golang / Backend Engineering

• Proven track record building production-grade Go applications
• Deep understanding of Go concurrency, memory management, error handling, context handling, and performance tuning
• Experience delivering REST APIs, gRPC services, backend workflows, and event-driven systems
• Strong software engineering fundamentals including clean code, testing, modular design, patterns, and maintainability
• Experience designing high-throughput, low-latency backend services
• Skill at debugging complex runtime and performance issues in Go

System Design & Architecture

• Strong system design and architecture capabilities
• Ability to design scalable, resilient, fault-tolerant, and secure distributed systems
• Deep knowledge of microservices, API design, event-driven and distributed systems, caching, asynchronous processing, database design, reliability, observability, and failure recovery
• Ability to evaluate tradeoffs across performance, scalability, security, reliability, maintainability, and delivery timelines
• Experience turning ambiguous requirements into clean technical designs and implementation plans