Senior Engineer

Bank of America•Pennington, AL

1d•$122,000 - $200,000•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!

Requirements

12+ years of software engineering experience, including significant experience as a senior technical lead and architect in complex enterprise environments.
Proven ability to design and deliver distributed systems, microservices, APIs, batch processing, data pipelines, rules engines, workflow services, and enterprise integrations at scale.
Strong hands-on experience with modern engineering stacks such as Java/Spring Boot, React, TypeScript, REST APIs, event streaming, SQL, Oracle or comparable relational databases, Redis or similar caching technologies, and automated testing frameworks.
Experience with cloud-native engineering practices, containerization, Kubernetes or OpenShift, CI/CD pipelines, infrastructure-as-code, observability, resiliency patterns, and secure software delivery.
Deep understanding of data modeling, data quality, ingestion patterns, reference data, auditability, lineage, and reporting or analytics integration.
Mentor engineers and technical leads, conduct design and code reviews, raise engineering maturity, and promote a culture of craftsmanship, ownership, and continuous improvement.
Influence cross-organization architecture decisions and communicate complex technical concepts clearly to senior business and technology stakeholders.

Nice To Haves

Frontend: React, TypeScript, reusable component models, accessibility-first design, and modern user experience patterns.
Backend and APIs: Java, Spring Boot, RESTful services, OpenAPI contracts, domain services, BFF/API façade patterns, and secure integration design.
Data and Processing: Oracle or comparable relational databases, data modeling, batch frameworks, event-driven ingestion, reference data, reconciliation, data quality, and lineage.
Platform: Red Hat OpenShift or Kubernetes, containers, CI/CD, GitOps, infrastructure-as-code, automated quality gates, and zero-touch deployment practices.
Integration: API gateway, service mesh, event streaming, enterprise messaging, CRM and underwriting integration, downstream booking and reporting integration.
Controls and Security: OAuth/OIDC, SSO, RBAC, entitlement services, secrets management, policy-as-code, vulnerability management, audit trails, and secure coding practices.
Observability and Resiliency: logging, metrics, tracing, dashboards, alerts, SLOs, synthetic monitoring, capacity planning, runbooks, and fault-tolerant design.
Automation
Influence
Result Orientation
Stakeholder Management
Technical Strategy Development
Application Development
Architecture
Business Acumen
Risk Management
Solution Design
Agile Practices
Analytical Thinking
Collaboration
Data Management
Solution Delivery Process

Responsibilities

Ensures that the design and engineering approach for complex features are consistent with the larger portfolio solution
Define the technology tool stack for the solution and evaluate and adapt new testing tool/framework/practices for team(s)
Enables team(s)/applications with Continuous Integration/Continuous Development (CI/CD) capabilities and engages with other technical stakeholders pertaining to efficient functioning of CI-CD pipeline
Guides and influences team(s) on design and best practices for high code performance –e.g. pairing, code reviews
Provides end-to-end delivery of complex features, including automation, for either a single team or multiple teams, at the program level
Conducts research, design prototyping and other exploration activities such as evaluating new toolsets and components for release management, CI/CD, and features
Works with stakeholders to establish high-level solution needs and with architects for technical requirements
Influence enterprise architecture decisions and communicate technology strategy effectively to senior business and technology stakeholders.
Define and evolve the architecture for commercial credit analysis, spreading, and pricing platforms, leveraging reusable services, Agentic AI, API-first design, event-driven architecture, strong data quality, and secure foundations.
Lead hands-on engineering delivery across full-stack, backend, data, workflow, integration, and cloud-native solutions.
Drive platform modernization in partnership with product, business, risk, architecture, and delivery leaders.
Establish and enforce engineering standards for quality, automation, resiliency, observability, CI/CD, security, and operational readiness.
Evaluate and implement modern technologies, including containerized services, Kubernetes/OpenShift, APIs, event streaming, databases, reporting platforms, and AI-enabled capabilities.
Partner with data and AI teams to deliver governed, explainable intelligence, digital assistants, semantic search, automated financial analysis, and analytics-driven insights.
Mentor engineering teams through design reviews, technical leadership, and continuous improvement initiatives to elevate engineering maturity.