Senior Java AWS Developer

• API Platform
• API Gateway + Java Lambdas
• ETL Platform
• AWS
• Glue for Job Scheduling and Loading
• ETL scripts (orchestrated by Glue)
• Observability and Monitoring
• AWS CloudWatch (Logs, Metrics, Alarms, Dashboards)
• Splunk (log search, SPL, saved searches)
• Datadog (APM, monitors, dashboards, log/metric exploration)
• Nice to Have Tech
• Adobe Experience Manager (AEM), backend/OSGi
• AI coding agents and agentic dev tools (e.g., Copilot agent mode, Claude Code)
• Harness (CI/CD, feature flags)

Java, Software Engineering, Amazon Web Services (AWS), Java, Amazon Web Services (AWS), Software Engineering, Software Development, Python Programming/Scripting Language, Cloud Applications, AWS Lambda, * 8+ years’’ experience in software development using Java, Springboot, Python and cloud application development

• Experience in Lambda function application development
• Thoughtful in approach to software engineering practices and should enable a future-ready, high quality, and responsive code base
• A strong understanding of Java programming
• A strong understanding of relational databases and SQL queries, Aurora DB desired
• Knowledge in Data structures, OOPs concepts, json/DB modeling
• A strong understanding and use of stateless asynchronous Restful API patterns
• Experience implementing AWS, Kubernetes CI/CD structures
• Hands-on experience with core AWS services (Lambda, API Gateway, S3, Glue, IAM, CloudFormation/CDK) for building and deploying serverless and ETL workloads
• Experience with AWS monitoring and observability tools (CloudWatch Logs, Metrics, Alarms, Dashboards) for tracking application health and performance
• Working knowledge of Splunk for log aggregation, SPL query writing, and troubleshooting production issues across distributed systems
• Experience with Datadog for APM tracing, custom metrics, dashboards, and monitor/alert configuration to proactively detect service degradation
• Ability to correlate logs and metrics across AWS CloudWatch, Splunk, and Datadog to perform root cause analysis during incidents
• Able to define, document and communicate, middleware and back-end architectures
• Clear communicator (written and verbal)
• Ability to focus on deadlines and deliverables
• Knowledge and understanding of Software development and Agile development and methodologies
• Agile mindset and passion for designing product user experiences enable rapid business growth
• Consultant thinker with ability to propose solution Eligible to workions

Nice to Have:

• Domain knowledge in Asset Management / Investment Management (portfolio positions, holdings, disclosures, fund/account structures)
• Experience with Adobe Experience Manager (AEM), including OSGi console, backend components/services, and Sling models
• Exposure to agentic development practices, using AI coding agents (e.g., GitHub Copilot agent mode, Claude Code) to autonomously plan, implement, and validate multi-step engineering tasks
• Experience with AI-driven testing, including LLM-based test case generation, automated defect triage, self-healing test scripts, and AI-assisted code review
• Familiarity with prompt engineering and orchestrating multi-agent workflows for software delivery (e.g., agent-driven code generation, review, and PR creation pipelines)
• Understanding of responsible AI usage in SDLC, including human-in-the-loop review, guardrails, and validation of AI-generated code/tests before production use
• Familiarity with financial data platforms and ETL for regulatory/disclosure reporting
• Knowledge of container orchestration tooling beyond basics (Helm charts, service mesh concepts)
• Exposure to feature flagging and progressive delivery practices (e.g., Harness Feature Flags)

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