Analyze existing systems to identify bottlenecks, tech debt, and implement scalability, and stability improvements.
Implement automation for testing, monitoring, healing, and scaling applications, continuous integration and deployment to reduce time to market.
Collaborate with cross-functional teams, including product managers, designers, and other engineers, to define and implement new features.
Conduct code reviews (comment, approve, seek revisions, merge), mentor junior and mid-level engineers, and actively promote engineering best practices.
Dive deep and troubleshoot complex issues, devise fixes, author root cause analysis documents, and ensure lasting performance and reliability.
Conduct objective and comparative analyses of competing technologies to advise the team of pros and cons of a technology solution.
Maintain robust documentation (design docs, run books, change management docs, and readiness plans).
Provide live-site support for production applications by monitoring systems, ensuring rapid incident resolution, and driving continuous improvement.
Drive cross-team projects as a single-threaded-owner (STO) or tech lead, and actively unblock other engineers to make progress.
Requirements
Bachelor’s degree in Computer Science or Software Engineering
5-8 years of professional experience in software engineering
Strong understanding of data structures and algorithms, object-oriented design, and problem-solving skills
Expertise in designing and developing internet-scale services with scalability, availability, security, and reliability design tenets
Excellent written and verbal communication skills, and a collaborative and empathetic mindset
Proficiency in backend development, with proficiency expertise in Java or C#, and frameworks like SpringBoot, building and optimizing RESTful APIs, ODATA framework, and SQL
Ability to leverage AI-enabled development tools such as Cursor AI, Kiro and GitHub Copilot to accelerate feature delivery, automate documentation, and enhance code quality.
Master’s degree in computer science or software engineering is preferred
10 years of experience in software engineering is preferred
Experience with event-driven architecture and tools like Kafka is preferred
Experience working on card payments is preferred
Familiarity with cloud-native architecture (containerization using tools such as Docker and Kubernetes) is preferred
Awareness of API security and PCI DSS compliance requirements is preferred
Familiarity with mobile development (iOS or Android) is preferred
Experience building AI skills & deploying AI solutions to production environments is preferred
Experience building production-grade AI agents or copilots is preferred
Familiarity with multi-agent systems and distributed AI architectures is preferred
Experience with vector databases (e.g., Pinecone, Weaviate, OpenSearch, Milvus) is preferred
Knowledge of AI evaluation techniques, safety practices, and responsible AI principles is preferred.