Develops secure and high-quality production code, and reviews and debugs code written by others
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 5+ years applied experience
Proficiency in back-end technologies (e.g., Java, Springboot, Node.js ) with experience building microservices-based applications for full-stack roles (e.g., HTML, CSS, JavaScript, Typescript, React, Angular)
Experience leading design and delivery of Kafka-based event streaming platforms/services in high-throughput (high TPS) environments (deep experience with event-driven architecture patterns and distributed systems reliability)
Demonstrated ability to independently solve design and functionality challenges with minimal supervision
Experience working with cloud platforms (e.g., AWS, Azure, GCP), distributed systems, and web technologies, including RESTful APIs and web services, WebSockets and JSON
Hands-on experience designing and building scalable applications using SQL and NoSQL databases
Proven ability to lead technical direction: drive architecture decisions, write/own design docs, align stakeholders, and deliver through ambiguity
Experience improving operability (SLOs/SLAs, on-call readiness, monitoring, incident response, postmortems) for streaming systems
Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Preferred qualifications, capabilities, and skills
Strong soft skills, including presentation, negotiation, mentoring, and stakeholder management
Strong problem-solving, analytical, and communication skills
Ability to drive broader impact by sharing and contributing best practices
AWS certification
Experience building and operating high-volume data processing pipelines using Apache Spark (Spark SQL, Structured Streaming) and/or Apache Flink (DataStream/Table API) in production.
