Software Engineer – Golang, System Design, Kubernetes Platform Development & AI Automation
Job Description:
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.
Key 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.
Required Qualifications:
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 and building 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.
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.
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 workload, API, networking, and platform integration issues.
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 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.
Differentiating Skills:
Candidates with the following experience will stand out:
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.
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/agentic programming.
They should be able to design and build scalable backend services, develop Kubernetes-native platform components, and use AI-driven automation to improve developer experience and operational efficiency. This person should think like a software engineer, architect like a systems designer, understand Kubernetes as a development platform, and be curious about how AI can transform platform engineering.
Shift:
1st shift (United States of America)Hours Per Week:
40Skills Required
- Strong hands-on experience developing production-grade applications in Go / Golang
- Deep understanding of Go concurrency patterns, goroutines, channels, interfaces, memory management, error and context handling, and performance tuning
- Experience building REST APIs, gRPC services, backend workflows, and event-driven systems
- Strong software engineering fundamentals: clean code, testing, modular design, dependency management, maintainability
- Experience designing and building high-throughput, low-latency backend services and debugging runtime, concurrency, memory, and performance issues
- Strong system design and architecture skills for scalable, resilient, fault-tolerant, secure distributed systems
- Knowledge of microservices, API design, event-driven architectures, caching, asynchronous processing, database design, reliability, observability, and failure recovery patterns
- Hands-on experience developing software that integrates with Kubernetes and familiarity with core Kubernetes concepts (Pods, Deployments, Services, Ingress, ConfigMaps, Secrets, Namespaces, RBAC)
- Experience with Kubernetes APIs and client libraries, preferably using Go (client-go, controller-runtime)
- Experience building Kubernetes controllers, operators, CRDs, and admission webhooks
- Practical experience using AI-assisted engineering tools and applying AI concepts to software development workflows
- Experience with Kubernetes operator development using Kubebuilder, Operator SDK, controller-runtime, or client-go
- Ability to troubleshoot complex production issues across Go services, Kubernetes workloads, APIs, networking, and distributed systems
- Practical experience with Red Hat OpenShift / OCP
- Experience building or integrating AI-powered automation, intelligent assistants, code analysis tools, or operational agents
- Experience with service mesh technologies (Istio, Consul, Linkerd)
- Experience with CI/CD and GitOps tools (Tekton, Argo CD, Jenkins, GitHub Actions)
- Experience with observability tools (Prometheus, Grafana, OpenTelemetry, Jaeger, Splunk, Dynatrace)
- Experience integrating with enterprise security platforms (Vault, Venafi, IAM, PKI)
- Experience with cloud or Kubernetes platforms (OpenShift, EKS, AKS, Rancher, Tanzu, 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
Bank of America Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Bank of America and has not been reviewed or approved by Bank of America.
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Fair & Transparent Compensation — The $25/hour U.S. minimum wage, reaffirmed in recent company materials, sets a clear compensation floor that lifts entry-level and operations pay. Public salary information and disclosures provide visible benchmarks for pay across roles.
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Parental & Family Support — Parental leave extends up to 26 weeks with 16 weeks fully paid for eligible teammates, alongside backup child and adult care and a dedicated Life Event Services team. Family-building assistance offers up to a $20,000 lifetime reimbursement and bereavement leave provides 20 paid days for loss of a spouse, partner, or child.
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Retirement Support — Retirement programs include a 401(k) match up to 5% of eligible pay plus an additional 2–3% annual company contribution based on service. These employer contributions add meaningful long-term value beyond base pay.
Bank of America Insights
What We Do
We make financial lives better for our clients and our communities through the power of every connection. Our employees are at the heart of this purpose, and are key to driving responsible growth. Every day, across the globe, our employees bring a commitment to our purpose and to driving responsible growth by living our values: deliver together, act responsibly, realize the power of our people and trust the team. A key aspect of driving responsible growth is doing so in a sustainable manner, a critical pillar of which is being a great place to work for our teammates.
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