Sr. Java Developer
Sharp Decisions San Jose
Position Overview
The Sr. Developer will deliver exceptional support to develop meaningful digital experiences and strengthen customer experience initiatives. The candidate will support digital applications across design, development, production support, and solutioning.
Key Responsibilities- 5-8+ years of professional software development experience with a strong focus on backend development using Java/J2EE, Spring Boot, Spring Data JPA, Hibernate, and related open-source frameworks.
- Strong hands-on experience designing, developing, and supporting cloud-native applications on AWS, utilizing services such as Lambda, API Gateway, EKS, ECS, S3, RDS, DynamoDB, SNS, SQS, EventBridge, Amazon MQ, MSK (Kafka), CloudWatch, and IAM.
- Proficient in microservices architecture, RESTful APIs, event-driven systems, and serverless application development, with a strong understanding of distributed systems design principles.
- Experience with containerization and orchestration technologies including Docker, Kubernetes, Amazon EKS, and/or Red Hat OpenShift.
- Strong understanding of Java fundamentals, JVM internals, concurrency, multithreading, performance optimization, and functional programming concepts such as Lambda Expressions, Streams API, and CompletableFuture.
- Experience with relational and NoSQL databases including Amazon RDS, PostgreSQL, MySQL, DynamoDB, and related data modeling and performance optimization techniques.
- Hands-on experience implementing CI/CD pipelines and DevOps practices using Jenkins, GitLab CI/CD, GitHub Actions, AWS CodePipeline, Terraform, CloudFormation, or similar technologies.
- Knowledge of cloud security and application security best practices including IAM, OAuth2, OpenID Connect, JWT, secrets management, encryption in transit and at rest, and secure API design.
- Strong problem-solving, debugging, troubleshooting, and performance tuning skills in large-scale production environments.
- Experience working in Agile/Scrum teams, participating in architecture discussions, code reviews, technical design, and mentoring junior engineers.
- Experience leveraging AI-assisted engineering tools such as GitHub Copilot, Amazon Q, Cursor, Claude, OpenAI, or similar technologies to improve development productivity, code quality, testing, documentation, and troubleshooting.
- Proficiency in Python and experience with AI/ML frameworks.
- Familiarity with enterprise AI/LLM concepts including Prompt Engineering, Retrieval-Augmented Generation (RAG), Vector Databases, Agentic Workflows, and Responsible AI practices.
- AWS, Kubernetes, AI/ML, or other relevant professional certifications.
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