Provide clear technical direction across architecture, engineering standards, platform design, technical risk and long-term maintainability.
Define appropriate service boundaries, APIs, event flows, integration patterns, data ownership and frontend integration approaches.
Lead significant technical decisions and design reviews, balancing delivery speed, security, resilience, scalability, operational needs and long-term value.
Work with the Software Architect to align major platform decisions with wider architectural principles and organisational direction.
Partner with the Software Development Manager and Lead Engineers to turn technical direction into practical delivery plans and sustainable execution.
Make high-leverage hands-on contributions through prototypes, reference implementations, critical-path work and support for complex technical problems.
Improve platform reliability, security, observability, performance, cloud maturity and operational readiness in AWS.
Strengthen engineering effectiveness through pragmatic standards, CI/CD, build and deployment practices, developer experience, testing and quality controls.
Identify and address material technical risks, dependencies, bottlenecks and architectural debt early.
Shape the effective and responsible use of AI-assisted development, selected AI agents and agent-enabled SDLC workflows.
Mentor engineers and Lead Engineers, raising technical capability, architectural judgement and engineering consistency.
Requirements
Essential Qualifications
Significant commercial software-engineering experience, including deep hands on experience with C# and .NET.
Experience owning or materially shaping the technical direction and architecture of complex production software platforms.
Strong experience designing APIs, distributed systems, event-driven architectures and service-based applications.
Sound judgement on service boundaries, asynchronous integration, event flows, data ownership and distributed-system trade-offs.
Strong experience with relational databases, ideally PostgreSQL.
Experience defining technical roadmaps, engineering standards, target architectures or technology strategy across multiple workstreams or teams.
Strong understanding of software design, testing, quality, security, observability, reliability and maintainable system design.
Experience with CI/CD, deployment pipelines, build automation and modern software-delivery practices; Jenkins experience is strongly preferred.
Experience making and communicating consequential technical trade-offs to both technical and non-technical stakeholders.
Experience improving engineering practices, developer experience and delivery effectiveness.
Practical experience using AI-assisted development tools and evaluating where AI-enabled engineering workflows create genuine value.
A track record of mentoring engineers and leading through influence rather than formal line management.
Desirable Qualifications
Experience with AWS, particularly Lambda, ECS, EC2 and cloud-native architectural patterns.
Experience with Docker, infrastructure as code and environment automation.
Experience with messaging, event streaming or other event-driven technologies.
Experience with BFF patterns, Blazor and MudBlazor.
Experience establishing architecture governance, decision records, technical standards or reference architectures.
Experience designing, operating or governing AI agents or LLM-enabled engineering workflows.
Experience in a growing product or platform-engineering environment. What Success Looks Like
The SaaS platform has a clear technical direction, target architecture and roadmap that support product ambition and sustainable growth.
Major technical decisions are timely, well understood, and balanced appropriately across speed, quality, risk and long-term maintainability.
The platform becomes increasingly scalable, secure, resilient, observable and operationally mature.
Engineers and Lead Engineers have clear technical guardrails, stronger engineering practices and greater confidence to make good decisions independently.
Material technical risks and architectural debt are identified early and addressed deliberately.
AI-assisted engineering and selected agent-enabled workflows deliver measurable practical value with appropriate quality and governance.
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We are dedicated to fostering a collaborative, engaging, and inclusive environment and are committed to providing a workplace that empowers associates to be authentic and bring their best to work. We believe that associates do their best when they feel safe, understood, and valued, and we work diligently and collaboratively to ensure Broadridge is a company—and ultimately a community—that recognizes and celebrates everyone’s unique perspective.
Use of AI in Hiring
As part of the recruiting process, Broadridge may use technology, including artificial intelligence (AI)-based tools, to help review and evaluate applications. These tools are used only to support our recruiters and hiring managers, and all employment decisions include human review to ensure fairness, accuracy, and compliance with applicable laws. Please note that honesty and transparency are critical to our hiring process. Any attempt to falsify, misrepresent, or disguise information in an application, resume, assessment, or interview will result in disqualification from consideration.
