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

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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 ArchitectureAPI DesignSystem DesignCI/CD Tools

ATS Keywords

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Hard Skills

Go Concurrency PatternsREST APIsGRPC ServicesEvent-Driven SystemsPerformance TuningMicroservices ArchitectureObservability PatternsKubernetes ControllersAutomation ToolingAI-Assisted Engineering

Soft Skills

Problem SolvingCollaborationTechnical Design

Tools & Technologies

KubernetesOpenShiftPrometheusGrafanaTektonArgo CDJenkinsGitHub ActionsIstioConsul

Certifications & Qualifications

Red Hat OpenShift/OCP

Industry Keywords

Financial ServicesRegulated Enterprise 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 supporting enterprise platform engineering capabilities
Develop Kubernetes-native components such as controllers, operators, CRDs, admission webhooks, and automation services
Build software integrating 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 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
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

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 architecture, API design, event-driven architecture, distributed systems, caching strategies, asynchronous processing, database design, reliability engineering, observability patterns, and 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
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, 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
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
Familiarity with LLM-based application patterns, prompt engineering, retrieval-augmented generation, tool/function calling, workflow orchestration, or autonomous task execution
Experience with Kubernetes operator development using Kubebuilder, Operator SDK, controller-runtime, or Kubernetes client-go
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
Red Hat OpenShift/OCP, AI-powered automation, intelligent assistants, code analysis tools, or operational agents are strongly preferred
40 hours per week

Benefits

Comp & perks

Annual discretionary incentive plan award eligibility
Benefits eligibility
Paid time off
Resources and support for employees
In-office flexibility based on role-specific responsibilities and business needs