Lead the rollout of BDD and SDD practices across product and engineering teams
Build SDD tooling that derives contract checks, mocks, and validation from machine-readable specs (OpenAPI/Swagger, JSON Schema, AsyncAPI for Kafka) as the source of truth.
Develops secure and high-quality production code, and reviews and debugs code written by others
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
Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 8+ years applied experience
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
Strong software engineer with hands-on experience using AI coding assistants/agents to design, implement, test, and debug production code
Proficient in Core Java, J2EE, and Spring Boot with strong coding skills.
Experienced in build and deployment processes
Knowledgeable in EKS, Kafka, and message parsers
Proficient in all aspects of the Software Development Life Cycle
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Preferred qualifications, capabilities, and skills
Experience using AWS - EKS and Bedrock
AI-Agentic approach in automation
Experience in performance engineering is a plus
