About the role
The Sr. Staff Engineer will be responsible for leading the architectural design and planning process for an enterprise application. This role involves collaboration with stakeholders and driving the strategic vision for the application. The candidate must be able to model customer requirements into existing and proposed new features of the application.
Responsibilities:
- Drive product innovation, technology roadmap, and provide long-term vision to developers.
- Author high-level design documents for microservices corresponding to cross-module design.
- Identify key performance parameters for the application and mechanisms to measure and report them.
- Develop simulations for breakthrough functional and technical performance.
- Incorporate proper certification/compliance requirements into the product designs.
- Participate in strategic planning for the product vision and roadmap.
- Lead PoC for new technologies to continuously improve technical platform and developer experience.
Requirements:
- Experience in development for scalable microservices-based distributed systems.
- Skilled in low-latency queuing systems.
- Background in microservices architecture.
- Skilled in REST API design.
- Experience with major architecture patterns.
- Well-versed in performance, scalability and observability.
- Ability to write clean design documents.
Qualifications:
- Education: Bachelor's or master's degree in Computer Science, Software Engineering, or a related field from a premier institute.
- Specialisation in computer science certifications is a bonus.
- Over 8 years of experience in the software industry, preferably 1+ years as an architect or Staff Engineer.
- Experience with frameworks and libraries relevant to the technology stack.
- Problem-Solving: Strong analytical and troubleshooting skills.
- Ability to diagnose and resolve complex problems in domains of algorithms, software integration, cloud and deployment.
Good to Have:
- Hands-on experience in deployment and performance tuning of databases, Kafka and Kubernetes clusters.
- Effective and innovative ways of using AI-based tools for enhanced developer experience.
- Data model-based and agentic development.