Java Engineer – SRE & GenAI

• Home • About • Adaptive AI • Industries • Consulting • Jobs Portal • Contact Us • Home • About • Adaptive AI • Industries • Consulting • Jobs Portal • Contact Us Job Description Job Overview • Job ID: J53593 • Job Title: Java Engineer – SRE & GenAI • Location: Charlotte, NC • Duration: 8 Months + Extension • Domain Exposure: Insurance • Work Authorization: US Citizen,Green Card,OPT-EAD,CPT,H-1B,H4-EAD,L2-EAD,GC-EAD • Client: To Be Discussed Later • Employment Type: W-2, 1099, C2C View All Jobs Similar Jobs • Java Backend Engineer - St Louis, MO • Senior Java Backend Developer - Phoenix,, AZ • Java Full Stack Developer - New York, NY • Java software Engineer - Houston, TX • Solution Architect with Java - Pittsburgh, PA Job Title: Java Engineer – SRE & GenAI Location: Charlotte, NC Duration: 8Months + Extension Bill Rate: $75/hour Job Type: C2C/1099 Contract Work Authorization: USC, GC, H-1B, OPT-EAD, GC-EAD, H4-EAD Job Summary We are looking for a hands-on Java + SRE Engineer with strong application development, production support, observability, and troubleshooting experience. The candidate should have solid Java/Spring Boot fundamentals along with practical knowledge of Generative AI and AI-assisted engineering tools to accelerate development, problem solving, automation, and learning of new technologies. Key Responsibilities • Develop, enhance, troubleshoot, and support enterprise applications using Java/J2EE, Spring Boot, REST APIs, and microservices. • Provide SRE and production engineering support for business-critical applications and services. • Troubleshoot complex production issues across application, API, infrastructure, database, and network layers. • Perform Root Cause Analysis (RCA) and drive corrective and preventive actions for recurring incidents. • Support Incident, Problem, and Change Management processes and work with application SLA/SLOs. • Monitor application and platform health using Splunk, Elasticsearch/Kibana, or similar observability platforms. • Create and enhance dashboards, alerts, log queries, and health monitoring. • Support applications running on Kubernetes/OpenShift and enterprise Linux environments. • Work with CI/CD pipelines, release/deployment processes, and production validation. • Identify opportunities to automate repetitive operational activities and improve application reliability. • Use AI-assisted engineering tools appropriately for code understanding, debugging, log analysis, documentation, testing, and automation. • Quickly ramp up on new applications, technologies, APIs, and support processes based on project requirements. Required Technical Skills Java / Application Engineering • Strong hands-on experience with Java/J2EE. • Strong knowledge of Spring Boot, REST APIs, and microservices. • Experience debugging production Java applications, including logs, exceptions, API failures, and performance issues. • Understanding of application design, integrations, and distributed systems. SRE / Production Engineering • Strong production support and troubleshooting experience. • Knowledge of Incident, Problem, and Change Management. • Experience with RCA, SLA/SLO, application availability, reliability, and production stability. • Ability to identify recurring operational issues and implement engineering or automation-based solutions. Observability • Hands-on experience with Splunk. • Knowledge of Elasticsearch/Kibana or similar observability tooling. • Experience with application monitoring, dashboards, alerts, log analysis, and production diagnostics. Cloud / Platform / DevOps • Good understanding of Kubernetes/OpenShift. • Knowledge of CI/CD pipelines, application deployments, and release management. • Understanding of networking, certificates, application connectivity, and traffic-routing concepts. • Scripting/automation experience is preferred. AI / GenAI Knowledge • Working knowledge of Generative AI, LLMs, and AI-assisted software engineering. • Experience using tools such as GitHub Copilot or equivalent AI coding assistants. • Ability to effectively use AI for: • Code understanding and development • Debugging and troubleshooting • Log and error analysis • Unit/test-case generation • Technical documentation • Script and automation development • Understanding unfamiliar applications and codebases • Basic understanding of prompt engineering and effective interaction with LLM-based tools. • Awareness of RAG, AI agents/agentic AI, and AI-assisted automation is a plus. • Ability to critically review and validate AI-generated code or recommendations before using them in production.