Must be hands on technical manager, who can jump in and code when needed but also able to provide technical direction, mentoring etc.
Bachelor's degree in Computer Science, Engineering, Information Technology, or related field required.
10-15 years of overall software engineering experience, with at least 6+ years on SAP Commerce / Hybris.5+ years of demonstrated business knowledge in the e-commerce / digital commerce domain.
10+ years of hands-on experience designing and delivering microservices on the Spring stack.10+ years in a leadership capacity managing engineering teams of 15+ members.
Proven track record of delivering large-scale SAP Commerce implementations with microservices integrations.
Hands-on background in Java 17/21, Spring Boot 3.x, Spring Framework 6.x, REST/gRPC APIs, and SAP Commerce extension development.
Experience with GraphQL and Domain-Driven Design (DDD).
Experience with SAP Commerce Cloud on Microsoft Azure, build manifests, and cloud operations.
Experience running production microservices on Kubernetes with mature CI/CD, GitOps, and observability practices.
Experience with Agile delivery models and modern DevOps tooling.
Technical/Functional Skills
Deep expertise in SAP Commerce architecture and integration patterns.
Proficiency with relational databases and search/indexing using Solr.
Strong hands-on experience designing and building microservices using the latest Spring ecosystem.
Expertise in Spring Cloud for service discovery, routing, and fault tolerance.
Proven ability to architect domain-driven, loosely coupled microservices.
Experience with reactive programming and event-driven architectures.
Hands-on with containerization, orchestration, and service mesh concepts.
Strong grounding in API security and zero-trust principles.
Experience integrating SAP Commerce with custom Spring Boot microservices.
Working knowledge of NoSQL stores
Practical, daily use of AI coding assistants and understanding of LLM fundamentals.
Ability to evaluate and integrate GenAI use cases into commerce.
Strong judgment on responsible AI use.
Leadership/Behavioral Competencies
Strong business acumen and strategic thinking.
Excellent stakeholder management and executive communication skills.
Decision-making under ambiguity and pressure.
Coaching mindset; ability to grow leaders and contributors.
Customer-first orientation balanced with engineering rigor.
Commercial awareness and bias for automation, simplification, and continuous improvement.