Professional Software Engineer - AI Driven Engineering (Hybrid - Newark, NJ, NYC or Edgewood, NY)

At Broadridge, we’ve built a culture where the highest goal is to empower others to accomplish more. If you’re passionate about developing your career, while helping others along the way, come join the Broadridge team.

Broadridge is hiring! We are seeking a Professional Engineer with advanced engineering and technical leadership position responsible for architecting, building, and overseeing highly scalable distributed systems and enterprise platforms. This role requires deep expertise in Java-based application development, event-driven architectures, cloud-native engineering, and large-scale data processing systems.

The ideal candidate possesses strong hands-on engineering capabilities across Kafka, AWS, PostgreSQL, microservices, APIs, and distributed systems design, while also leading and overseeing delivery execution across multiple engineering teams.

Technology Development is responsible for the design, development, testing, implementation, and support of enterprise applications and distributed platforms that enable critical business processing and services. This includes business analysis, software engineering, cloud architecture, platform modernization, operational support, and continuous improvement through automation and AI-assisted engineering practices.

Responsibilities

• Design, develop, and implement scalable, resilient, and high-performance enterprise applications and distributed systems using Java and modern cloud-native technologies.
• Lead the architecture and development of event-driven systems leveraging Kafka, microservices, asynchronous processing, and distributed messaging patterns.
• Build and support applications and platforms within AWS environments utilizing services such as EKS, ECS, MSK, Aurora Postgres, S3, Lambda, and related AWS technologies.
• Design and optimize relational data models, SQL queries, and large-scale transactional processing solutions using PostgreSQL and related database technologies.
• Develop REST APIs, backend services, integration frameworks, and real-time data processing solutions supporting enterprise-scale workloads.
• Lead technical design reviews, engineering standards, architecture governance, and delivery oversight across multiple engineering squads and vendor teams.
• Oversee end-to-end delivery execution, ensuring alignment across architecture, development, testing, DevOps, operational readiness, and production support activities.
• Create, review, and enforce automated testing strategies including unit tests, integration tests, functional tests, API tests, and BDD-based validation approaches.
• Ensure software quality through CI/CD automation, DevSecOps practices, observability, monitoring, resiliency testing, and operational excellence standards.
• Lead troubleshooting, root cause analysis, performance tuning, and resolution of complex distributed system and production issues.
• Mentor engineers and provide technical leadership across teams while promoting engineering best practices, modernization strategies, and AI-assisted software delivery capabilities.
• Collaborate with business stakeholders, architects, product owners, infrastructure teams, and engineering leadership to deliver strategic technology initiatives.

AI-Driven Engineering Requirements AI-assisted software engineering is considered a core competency for this role. Candidates must demonstrate strong hands-on experience using modern AI tooling to accelerate software delivery, engineering productivity, testing, and operational efficiency.

Required experience includes:

• Daily use of AI-assisted development tools such as GitHub Copilot, Claude Code, OpenAI Codex, or equivalent platforms.
• Proven ability to leverage AI tooling to accelerate software design, code generation, refactoring, debugging, testing, and documentation creation.
• Experience using AI tools to generate and enhance unit tests, integration tests, functional tests, API specifications, BDD scenarios, and technical documentation.
• Ability to establish and promote AI-assisted engineering best practices across multiple teams while maintaining strong standards for architecture, quality, maintainability, and security.
• Strong understanding of governance, risk management, and operational considerations associated with AI-generated code and software artifacts.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related discipline.
• Exten…