Responsibilities of the Candidate:

Lead complex software engineering initiatives with significant business impact.
Define and execute technology strategy, architecture roadmaps, and modernization programs.
Design, develop, and deliver scalable, high-performance, cloud-native applications and APIs.
Drive decomposition of monolithic platforms into reusable microservices and domain-driven architectures.
Partner with Product Managers, TPMs, Architects, and Engineering teams to translate business requirements into technical solutions.
Evaluate emerging technologies, AI capabilities, and third-party platforms to improve business outcomes and engineering efficiency.
Develop Proofs of Concept (POCs) and validate new architectural approaches.
Champion engineering excellence through code reviews, design reviews, automated testing, and continuous improvement.
Drive adoption of AI-powered development tools and practices to improve developer productivity, code quality, testing efficiency, documentation, and operational excellence.
Mentor engineers, foster technical growth, and promote a culture of innovation and continuous learning.
Communicate architecture decisions, risks, trade-offs, and technical strategies effectively to leadership and stakeholders.
Ensure adherence to security, compliance, quality, reliability, and software development standards.

Requirements:

Bachelor's degree in Computer Science, Engineering, Information Technology, or equivalent practical experience.
Extensive experience designing, developing, and leading enterprise-scale software platforms.
Strong expertise in Java, Spring Boot, REST APIs, Microservices, PostgreSQL, and distributed systems.
Experience building secure, resilient, high-availability applications in cloud environments.
Proven ability to architect and deliver mission-critical systems at scale.
Experience integrating external APIs, payment platforms, SaaS products, and third-party services.
Strong understanding of software architecture patterns, domain-driven design, event-driven architectures, and API-first development.
Hands-on experience with Agile, DevSecOps, CI/CD, infrastructure automation, and cloud-native engineering practices.
Experience leveraging AI-assisted development tools such as GitHub Copilot, AI coding assistants, intelligent code generation, automated testing, and developer productivity platforms.
Demonstrated ability to learn, evaluate, and adopt emerging technologies, frameworks, and AI innovations.
Strong leadership, communication, collaboration, and stakeholder management skills.