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

Bank of America is seeking a Senior Software Engineer specializing in Golang, system design, Kubernetes platform development, and AI automation to build enterprise-scale backend services.

Responsibilities

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

• Proven hands-on experience building production-grade Go applications.
• Deep understanding of Go concurrency patterns, goroutines, channels, interfaces, memory management, error handling, context handling, and performance tuning.
• Experience delivering REST APIs, gRPC services, backend workflows, and event-driven systems.
• Solid software engineering fundamentals including clean code, testing, modular design, design patterns, dependency management, and maintainability.
• Experience designing high-throughput, low-latency backend services.
• Ability to diagnose complex runtime, concurrency, memory, and performance issues in Go applications.
• Strong system design and architecture capabilities.
• Ability to design scalable, resilient, fault-tolerant, and secure distributed systems.
• Extensive understanding of microservices, API design, event-driven architecture, distributed systems, caching, asynchronous processing, database design, reliability engineering, observability patterns, and failure recovery.
• Ability to evaluate tradeoffs across performance, scalability, security, reliability, maintainability, and delivery timelines.
• Experience converting ambiguous requirements into clean technical designs and implementation plans.
• Hands-on experience developing software that integrates with Kubernetes.
• Strong knowledge of Kubernetes architecture and core concepts including Pods, Deployments, Services, Ingress, ConfigMaps, Secrets, Namespaces, RBAC, CRDs, Controllers, Operators, and admission controllers / webhooks.
• Experience using Kubernetes APIs and client libraries, preferably with 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 workloads, APIs, networking, and platform integrations.
• 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 AI use cases that improve engineering productivity, reduce manual effort, or enhance platform operations.
• Familiarity with LLM-based patterns such as prompt engineering, retrieval-augmented generation, tool calls, workflow orchestration, and 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, and 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.
• Expert-level Go engineering experience 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 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
• Istio, Consul, Linkerd
• Prometheus, Grafana, OpenTelemetry, Jaeger, Splunk, Dynatrace
• Vault, Venafi, IAM, PKI
• EKS, AKS, Rancher, Tanzu, GKE
• AI frameworks, agent orchestration, vector search, embeddings

Shift

1st shift (United States of America)

Hours per Week

40

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 and agentic programming.

Differentiating Skills

• Expert level Go engineering with deep 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 tradeoffs clearly.

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 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 backlog generation, knowledge extraction, operational troubleshooting, platform support automation, and intelligent runbook execution.

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 workloads, API, networking, and platform integration issues.

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 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.
• Solid grasp of microservices, API design, event-driven architecture, distributed systems, caching strategies, asynchronous processing, database design, reliability engineering, observability, and failure handling patterns.
• Ability to evaluate technical tradeoffs across performance, scalability, security, reliability, maintainability, and delivery timelines.
• Experience translating ambiguous requirements into clean technical designs and implementation plans.