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Bank of America

Software Engineer – Golang, System Design, Kubernetes, AI Automation

Bank of America

. Design, develop, and maintain backend services, platform APIs, automation frameworks, and developer-facing services using Golang .

Posted 9/29/2026full-timeJersey City • New Jersey • United StatesMid-LevelSenior💰 $88,800 - $144,800 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing scalable, resilient, and secure distributed systems using Go, Kubernetes, and API design principles. Proficient in building automation frameworks and integrating with enterprise infrastructure while applying strong system design and architecture skills.

Highest-signal resume keywords
Golang DevelopmentKubernetes IntegrationAPI DesignSystem DesignAutomation Frameworks

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Go Concurrency PatternsREST APIsGRPC ServicesEvent-Driven SystemsPerformance TuningMicroservicesObservabilityDatabase DesignAI-Assisted EngineeringService Mesh Technologies
Soft Skills
CollaborationProblem-SolvingDebugging
Tools & Technologies
KubernetesOpenShiftCI/CD ToolsObservability ToolsAI Frameworks
Industry Keywords
Financial ServicesRegulated Environment

Tech Stack

Tools & technologies
CloudConsulDistributed SystemsGrafanaGRPCJenkinsKubernetesMicroservicesOpenShiftPrometheusSplunkVaultGo

About the role

Key responsibilities & impact
  • Design, develop, and maintain backend services, platform APIs, automation frameworks, and developer-facing services using Golang
  • Build scalable, resilient, and secure distributed systems for enterprise platform engineering
  • Develop Kubernetes-native components such as controllers, operators, CRDs, admission webhooks, and automation services
  • Integrate software 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 system design principles covering scalability, resiliency, concurrency, caching, reliability, fault tolerance, and performance optimization
  • Use AI-assisted and agentic programming approaches to improve productivity, automate platform tasks, and enhance developer experience
  • Build intelligent automation such as code analysis agents, remediation workflows, backlog generation, operational assistants, and developer self-service agents
  • Troubleshoot complex production issues across Go services, Kubernetes workloads, APIs, networking, and distributed systems
  • Participate in architecture reviews and define engineering standards for Go-based platform services
  • Collaborate with platform engineering, SRE, security, DevOps, AI engineering, and application teams

Requirements

What you’ll need
  • 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
  • Strong system design and architecture skills
  • Ability to design scalable, resilient, fault-tolerant, and secure distributed systems
  • Understanding of microservices, API design, event-driven architecture, distributed systems, caching, asynchronous processing, database design, reliability engineering, observability, and failure recovery
  • Ability to evaluate technical tradeoffs across performance, scalability, security, reliability, maintainability, and delivery timelines
  • Experience converting ambiguous requirements into technical designs and implementation plans
  • Hands-on experience developing software that integrates with Kubernetes
  • Understanding of Kubernetes architecture and core concepts, including 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 strongly preferred
  • Ability to troubleshoot Kubernetes workload, API, 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 strongly preferred
  • Familiarity with LLM application patterns, prompt engineering, retrieval-augmented generation, tool/function calling, workflow orchestration, or autonomous task execution
  • Experience with Kubebuilder, Operator SDK, controller-runtime, or Kubernetes client-go
  • Experience with OpenShift 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

Benefits

Comp & perks
  • Annual discretionary incentive plan eligibility
  • Benefits eligibility
  • Paid time off
  • Resources and support for employees
  • In-office culture with role-specific flexibility