This leader will build and develop a high-performing SRE team while remaining deeply engaged in architecture, software engineering, automation, and production performance. Partnering with application engineering, product, architecture, security, and operations, the Senior Manager will ensure that reliability is engineered into services from design through deployment and ongoing operation.

The role requires strong technical depth in Java, Spring Boot, AWS, Kafka, and PostgreSQL, combined with demonstrated people leadership and delivery accountability. DevOps practices, release automation, and responsible AI enablement will be central to improving engineering productivity and production outcomes.

Job responsibilities:

• Build and lead a high-performing SRE team. Own hiring, coaching, performance management, career development, and succession planning. Establish clear technical expectations, strengthen engineering judgment, and maintain sustainable operational and on-call responsibilities.
• Own the SRE strategy and execution roadmap. Translate platform and business priorities into measurable improvements in reliability, release performance, automation, and scalability. Manage capacity, dependencies, and delivery commitments while protecting time for engineering improvements.
• Remain hands-on in engineering decisions. Lead architecture and code reviews, guide complex troubleshooting, and contribute to critical automation and tooling. Ensure operational software meets the same standards for testing, security, maintainability, and documentation as application code.
• Advance AWS infrastructure and platform automation. Develop reusable infrastructure-as-code patterns, consistent environment configurations, and automated provisioning and recovery. Strengthen IAM, networking, compute resilience, and capacity management across the platform’s AWS services.
• Improve Kafka reliability and event-processing performance. Address partitioning, consumer-group behavior, consumer lag, schema evolution, delivery semantics, replay, and failure recovery. Validate that recovery approaches preserve intended processing behavior and data integrity.
• Strengthen PostgreSQL performance and resilience. Partner with application and database engineers on schema design, indexing, query optimization, transaction behavior, connection pooling, safe migrations, and recovery testing.
• Lead release engineering and deployment readiness. Improve CI/CD pipelines through automated testing, security checks, artifact traceability, and production validation. Establish safe deployment and rollback or roll-forward patterns that account for API compatibility, database changes, and event-schema dependencies.
• Make service health measurable. Define service-level indicators, service-level objectives, and error-budget practices with service owners. Use metrics, logs, and distributed traces to improve detection, reduce alert noise, and prioritize engineering work based on business impact.
• Reduce operational toil through automation. Build reusable tooling, self-service capabilities, and controlled remediation for well-understood failure scenarios. Measure reductions in manual effort, recurring incidents, and recovery time.
• Enable practical, responsible AI adoption. Integrate approved AI tools into code and test development, infrastructure review, knowledge retrieval, and incident investigation. Validate outputs, measure benefits, protect sensitive information, and retain appropriate human review and authorization for production changes.
• Lead incident resolution and resilience improvement. Coordinate technical response to complex incidents, communicate impact and recovery progress, and drive blameless reviews and permanent corrective actions. Validate capacity, failover, backup restoration, and disaster recovery against agreed objectives.
• Influence cross-functional decisions. Communicate technical risk and investment trade-offs to senior stakeholders. Resolve competing priorities and establish shared accountability for production readiness, secure delivery, and reliable service operation.

Leadership and professional capabilities

• Functional knowledge: Deep software and reliability engineering expertise, with sufficient breadth across cloud infrastructure, data platforms, security, and operations to guide end-to-end technical decisions.
• Business expertise: Understand how platform failures and delivery constraints affect clients and business services. Anticipate operational and regulatory risks and translate them into practical engineering priorities.
• Leadership: Deliver through others without becoming detached from the technology. Develop technical leaders, delegate meaningful ownership, and hold teams accountable for engineering quality and measurable outcomes.
• Problem solving: Resolve complex, cross-service problems using evidence, experimentation, and sound technical judgment. Favor durable engineering solutions over repeated manual intervention.
• Interpersonal skills: Explain complex technical issues clearly, constructively challenge assumptions, and influence senior stakeholders across organizational boundaries.

Required qualifications:

• 10+ years of software engineering or closely related production engineering experience, including substantial experience building and operating Java-based services in production.
• Demonstrated engineering people-management experience, including hiring, performance management, talent development, resource planning, and accountability for complex technical delivery. Experience leading senior engineers and developing technical leads.
• Strong Java and Spring Boot skills, including API design, concurrency, performance tuning, automated testing, and secure coding. Ability to review application code and diagnose runtime behavior rather than relying solely on infrastructure-level investigation.
• Hands-on AWS experience deploying and operating services, with knowledge of IAM, networking, observability, infrastructure as code, and at least one compute platform such as ECS, EKS, or Lambda.
• Production Kafka experience covering event-driven design, consumer groups, partitioning, schema evolution, delivery semantics, and failure recovery.
• Strong PostgreSQL skills in schema design, indexing, query optimization, transactions, migrations, and operational troubleshooting.
• Demonstrated ability to build maintainable automation and operational tooling using sound software engineering practices, including version control, peer review, automated testing, and reusable design.
• Experience with CI/CD, release engineering, automated testing, monitoring, incident response, and reliable distributed-system design.
• Practical understanding of service-level objectives, capacity planning, production readiness, recovery strategies, and the use of delivery and reliability measures to guide improvement.
• Ability to lead technical design reviews, mentor engineers, and communicate architectural, operational, and delivery trade-offs with product, security, operations, and senior technology leaders.

Preferred qualifications

• Experience with Kubernetes, Terraform, OpenTelemetry, Kafka Connect, and PostgreSQL replication or high availability.
• Experience designing and operating platforms with clearly defined service-level objectives, capacity plans, and tested disaster-recovery procedures.
• Experience implementing progressive delivery, automated release verification, self-service engineering tools, or policy-as-code controls.
• Experience introducing AI-assisted engineering or operational capabilities with demonstrated improvements in productivity, quality, or incident resolution, supported by appropriate evaluation and safeguards.
• Experience supporting financial-services platforms or other regulated, business-critical distributed systems

"Broadridge considers various factors when evaluating a candidate's final salary including, but not limited to, relevant experience, skills, and education."

 Salary Range: 235,000.00 – 250,000.00 USD annual

Bonus Eligible

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