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

Bank of America•Chandler, AZ

30d•Onsite

About The Position

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day. Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits. We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve. Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs. At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us! Position Summary: We are 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 requires someone who can go beyond writing application code — someone who can build intelligent, scalable, enterprise-ready platform capabilities. This role is focused on building scalable backend services, platform APIs, Kubernetes-native automation, and intelligent developer platform capabilities. The ideal candidate is a strong software engineer who can design and build reliable distributed systems in Go, develop software that integrates deeply with Kubernetes, and leverage AI/agentic programming concepts to improve automation, developer productivity, operational workflows, and platform intelligence. This is not a traditional DevOps, Kubernetes administrator, or basic scripting role. We are looking for an engineer who can write production-grade Go code, design complex systems, build Kubernetes-native components, and apply modern AI-assisted engineering techniques to solve real enterprise platform challenges.

Requirements

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.
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.
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 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.
Ability to identify use cases where AI can improve engineering productivity, reduce manual effort, or enhance platform operations.

Nice To Haves

Practical experience with Red Hat OpenShift / OCP is strongly preferred.
Experience building or integrating AI-powered automation, intelligent assistants, code analysis tools, or operational agents is strongly preferred.
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, 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 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.

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.