Sr. Staff Software Engineer- Java/AI

Serve as a subject matter expert and trusted technical advisor for complex systems, architecture, and engineering challenges. Lead the architecture, design, development, and evolution of large-scale, cross-domain software systems and platform capabilities supporting payroll, compliance, and enterprise applications. Develop technical strategies for initiatives with substantial complexity, integration requirements, risk, and customer impact. Drive architectural decisions that improve scalability, reliability, maintainability, security, performance, and operational efficiency. Apply deep technical expertise and advanced engineering principles to solve unique and complex problems affecting multiple teams or capabilities. Evaluate architectural trade-offs and technology choices while balancing immediate business requirements with long-term platform strategy. Partner with architects, engineering leaders, product leaders, and other stakeholders to evolve platform architecture and technical roadmaps. Anticipate emerging technical challenges and identify opportunities to introduce new technologies, architectural patterns, and engineering practices. Influence architectural standards and engineering decisions across the Value Stream. Software Development Drive the development strategy for large-scale, complex, and cross-domain modules, services, and sub-systems. Design and develop highly scalable backend APIs, distributed systems, cloud-native services, and high-volume data processing capabilities. Deliver high-quality, maintainable, secure, testable, and observable software using modern engineering practices. Establish and reinforce best practices for software design, coding, testing, performance, maintainability, and operational readiness. Lead strategic code, design, and test-plan reviews and raise the engineering quality bar across teams. Drive modernization and technical-debt reduction initiatives that improve platform sustainability, developer productivity, and customer experience. Remain hands-on with critical technical challenges, prototypes, complex implementations, and production problems where deep expertise is required. AI-First Engineering & Innovation Champion an AI-first engineering culture and drive effective and responsible adoption of AI across engineering workflows. Identify opportunities to use AI across requirements analysis, architecture, software development, testing, documentation, troubleshooting, observability, and operational workflows. Evaluate emerging capabilities in Generative AI, AI-assisted software development, agentic systems, and intelligent automation and determine their applicability to business and engineering challenges. Lead proofs of concept and technical experiments that translate emerging AI capabilities into practical engineering solutions. Develop reusable AI-enabled tools, patterns, or practices that can scale beyond an individual team. Measure the impact of AI initiatives through outcomes such as engineering effort saved, cycle-time improvement, automation gains, quality improvement, or reduction in operational effort. Mentor engineers on effective, secure, and responsible use of AI throughout the SDLC. Stay current with emerging AI and technology trends and provide technical recommendations on where engineering practices and architecture should evolve. Take ownership of the health, reliability, scalability, observability, and production readiness of business-critical services. Actively participate in production support and on-call responsibilities and provide technical leadership during complex incidents. Lead incident response across services, coordinating investigation, mitigation, communication, recovery, and follow-up actions. Lead root cause analysis for significant production incidents and drive systemic corrective and preventive actions. Establish and champion observability practices using telemetry, metrics, logs, traces, dashboards, and actionable alerting. Identify recurring failure patterns and drive architectural or engineering improvements that prevent customer impact. Partner with SRE, platform, and engineering teams to improve operational maturity and system resiliency. Influence service-health and reliability practices beyond the immediate team. Bachelor's degree in Computer Science, Engineering, or related technical field. 12+ years of professional software engineering experience, including significant experience designing and leading complex enterprise software systems. Proven experience architecting and delivering scalable backend services, APIs, distributed systems, and enterprise applications. Strong understanding of distributed-system architecture, design patterns, scalability, resiliency, concurrency, performance, and data consistency. Hands-on experience with cloud platforms such as GCP, AWS, or Azure. Experience with distributed caching technologies such as Redis and/or Hazelcast. Strong experience with observability platforms including Grafana, Kibana, OpenTelemetry, or similar technologies. Proven ability to lead large, technically complex initiatives involving multiple teams, services, or domains. Demonstrated ability to develop technical strategy and translate broadly defined business outcomes into executable technical solutions. Proven experience leading resolution of complex production incidents and driving root cause analysis and preventive improvements. Strong understanding of CI/CD, DevOps practices, production operations, and service ownership. Strong understanding of secure software development and handling of sensitive customer data. Demonstrated AI-first engineering mindset with hands-on experience applying AI-assisted development tools and workflows to real engineering problems. Demonstrated ability to mentor engineers and influence technical decisions beyond the immediate team. Strong customer and business mindset with the ability to connect technical decisions to customer and organizational outcomes. Excellent communication skills with the ability to explain complex technical concepts, influence stakeholders, and build alignment across teams. Demonstrated ability to operate independently and exercise sound technical judgment in ambiguous and highly complex situations. Experience in payroll, tax, HR, fintech, compliance, financial systems, or other highly regulated domains. Strong understanding of U.S. and/or Canadian payroll processing concepts. Experience designing and evolving cloud-native microservices and distributed architectures at enterprise scale. Deep understanding of CI/CD, Infrastructure as Code, deployment architecture, and modern DevOps practices. Experience leading major architectural transformations, platform modernization, or complex system migrations. Experience establishing observability, service-health, and operational-excellence standards across multiple teams. Experience with performance engineering and optimization of large-scale distributed applications. Experience designing resilient systems using patterns such as asynchronous processing, event-driven architecture, caching, fault tolerance, and graceful degradation. Experience driving adoption of AI-assisted engineering practices and demonstrating measurable improvements in engineering productivity or quality. Experience developing AI agents, engineering automation, or AI-enabled developer productivity solutions. Demonstrated ability to identify emerging technologies and translate them into practical engineering solutions. Experience influencing technical roadmaps and engineering strategy across multiple teams or a Value Stream. Demonstrated technical thought leadership through architecture forums, technical publications, internal engineering communities, patents, conference participation, or similar contributions. Ensure architecture and applications adhere to secure coding practices, privacy requirements, and applicable compliance standards. Drive secure handling of payroll, tax, financial, and personally identifiable information (PII). Incorporate security, privacy, auditability, and data-governance considerations into architecture and technical design from the beginning. Identify security and compliance risks associated with architectural and technology decisions and drive appropriate mitigation strategies. Advocate for security-by-design and privacy-by-design principles throughout the software development lifecycle. Technical Strategy & Continuous Engineering Understand product, engineering, and business strategy and translate strategic objectives into technical direction and execution. Identify emerging technology trends and evaluate how they can improve products, platforms, engineering practices, or customer outcomes. Develop advanced technical ideas and guide them from experimentation through adoption and production implementation. Anticipate significant technical and business challenges and develop solutions aligned with long-range objectives. Champion new tools, technologies, and engineering practices and help scale successful approaches across teams. Articulate trade-offs between short-term technical solutions and long-term architectural sustainability, ensuring risks are clearly understood by stakeholders. Influence prioritization of technical investments based on customer impact, operational risk, engineering efficiency, and long-term platform health. Mentorship & Engineering Excellence Act as a technical mentor and role model for engineers across multiple experience levels. Mentor engineers through architecture discussions, design reviews, code reviews, troubleshooting, and technical decision-making. Help develop senior engineers into stronger technical leaders and independent problem solvers. Promote a culture of continuous learning, experimentation, accountability, collaboration, and engineering excellence. Lead architecture and technical knowledge-sharing sessions and ensure important architectural decisions and learnings are documented. Build technical communities and relationships across teams to promote reuse of engineering patterns, knowledge, and best practices. Participate in technical interviews and help maintain a high engineering hiring bar. Provide clear, evidence-based hiring feedback and help other engineers improve their interviewing capabilities. Unified Engineering Ownership Demonstrate end-to-end ownership across requirements, architecture, design, development, testing, deployment, observability, incident response, and continuous improvement. Lead large initiatives, programs, or multiple projects with substantial technical risk, complexity, integration requirements, and organizational visibility. Develop execution strategies for broadly defined outcomes and independently determine technical objectives, approaches, and methods. Identify cross-team dependencies and risks early and drive alignment and resolution. Influence technical execution across multiple teams without relying on formal authority. Partner with Product, Architecture, Compliance, Customer Support, SRE, and other engineering teams to deliver customer-focused solutions. Establish accountability and engineering ownership throughout the lifecycle of capabilities being delivered. Customer & Business Mindset Develop deep understanding of the business domain and how customers use the capabilities and systems being designed. Connect architecture and engineering decisions to customer experience, business outcomes, reliability, compliance, and operational impact. Partner with Product and business stakeholders to understand customer problems and help shape technical solutions and capability direction. Use telemetry, product analytics, monitoring, operational data, and customer feedback to understand how capabilities behave in production. Anticipate customer impact when introducing architectural changes, new capabilities, migrations, or technology transformations. Act as a trusted technical advisor on complex customer and business challenges. Ensure monitoring, telemetry, and operational readiness are considered from the beginning of solution design rather than after deployment.