About the role
Requirements:
- 4-7 years of hands-on experience in software development with strong expertise in Java (preferably Java 21), microservices, and REST APIs.
- Experience with frameworks such as Spring Boot, Quarkus, and Hibernate, and understanding of backend/frontend technologies.
- Strong knowledge of cloud-native development on AWS (Lambda, EC2 S3 Kubernetes, Docker, etc. ).
- Understanding of Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, vector databases, and AI orchestration concepts.
- Experience integrating enterprise AI services and AI APIs into business applications.
- Knowledge of AI agent architectures, intelligent workflow automation, and modern AI application patterns.
- Understanding of ontology, semantic models, metadata-driven architectures, knowledge graphs, and enterprise knowledge management concepts.
- Understanding of AI evaluation techniques, prompt engineering, model selection, and AI application observability.
- Knowledge of Responsible AI principles includes fairness, transparency, explainability, privacy, accountability, and compliance.
- Experience designing and implementing microservices architectures and serverless solutions.
- Proficiency in CI/CD, DevOps practices, and tools (GitLab CI, Maven/Gradle, Nexus, SonarQube, and Veracode).
- Strong expertise in relational (Postgres, MySQL, Aurora) and NoSQL databases (DynamoDB, MongoDB, Redis), including query optimization.
- Solid understanding of authentication/authorization mechanisms (OAuth 2.0 OpenID Connect, IAM).
- Experience in monitoring, debugging, and troubleshooting production systems.
- Strong commitment to code quality, test automation (JUnit/PyTest), and secure coding practices.
- Understanding of AI security risks, including prompt injection, jailbreak attacks, adversarial inputs, model abuse, sensitive data exposure, and AI governance controls.
- Ability to implement AI guardrails, monitoring, auditability, and secure AI application development practices.
- Proven ability to mentor developers, perform code reviews, and drive engineering excellence.
- Hands-on experience with Agile methodologies and the end-to-end software development lifecycle.
- Excellent problem-solving skills, strong ownership mindset, and ability to work in a fast-paced environment.
- Embraces diverse people, thinking, and styles.
- Consistently makes the safety and security of self and others the priority.