Software Developer Advanced for Support Engineering

Software Developer Advanced for Support Engineering Siemens Digital Industries Software | Posted Mar 9 | Full‑time | Charlotte | Negotiable | Advanced (5‑10 yrs) We are a leading global software company dedicated to the world of computer‑aided design, 3D modeling and simulation—helping innovative global manufacturers design better products, faster! With the resources of a large company and the energy of a software start‑up, we have fun together while creating a world‑class software portfolio. Our culture encourages creativity, welcomes fresh thinking, and focuses on growth, so our people, our business, and our customers can achieve their full potential. Position Overview As part of the Siemens cloud operations organization, this position contributes to the delivery of best‑in‑class cloud‑based applications. The developer will design, develop, maintain and support internal tools and offerings, focusing on automating routine tasks and improving the developer experience. Responsibilities Platform Development & Operations Design, develop and customize platforms to serve as developer portals for internal teams. Integrate R&D tools and services for seamless developer onboarding experience. Container Orchestration, Infrastructure as Code & CI/CD Pipelines Use Infrastructure as Code best practices to create automated infrastructure within cloud and on‑premise platforms. Implement and maintain CI/CD tools and processes to support development, QA, and customer value realization teams. Manage service‑critical codebase with version control using Git including GitLab or GitHub. Support Engineering Provide L1 support: respond to service requests, perform basic troubleshooting, access management, and monitor system health dashboards. Provide L2 support: conduct in‑depth technical analysis, troubleshoot complex platform issues, perform log analysis and debugging. Provide L3 support: lead major incident response, conduct comprehensive root cause analysis (RCA), and implement permanent solutions. Participate in on‑call rotation to provide 24×7 support coverage for production systems. Develop and maintain support tools, scripts, runbooks, and knowledge base articles. Track and report on support metrics including ticket volume, resolution time, SLA compliance, and customer satisfaction. AI‑Powered Support & Intelligent Automation Implement AI‑driven incident triage, classification, and automated ticket routing systems. Develop intelligent chatbots and virtual assistants to handle L1 support queries and provide instant resolution. Build AI‑powered anomaly detection and predictive models to proactively identify potential failures. Implement automated root cause analysis using AI/ML to accelerate troubleshooting and reduce MTTR. Create self‑healing automation workflows using AI to detect, diagnose, and remediate common issues. Build RAG (Retrieval‑Augmented Generation) systems for intelligent knowledge base search and troubleshooting guidance. Implement intelligent alert correlation systems to reduce alert fatigue and improve signal‑to‑noise ratio. Leverage AI for automated incident report generation, post‑mortem analysis, and preventive action recommendations. Education and Experience Bachelor’s degree in Computer Science, Engineering, or equivalent. 6–8 years of related experience. 3 years of Software Development Life Cycle (SDLC) experience. 3 years of experience delivering enterprise‑grade cloud and SaaS applications. 2+ years of experience in production support engineering with L2/L3 support responsibilities. Required Skills Core Technical Skills AWS certification and Kubernetes certification. Strong proficiency in Java, Python and Go. Hands‑on experience with Kubernetes, Docker, cloud platforms (AWS or Azure). Proficient in API development (RESTful and GraphQL), microservices architecture. Expertise in GitLab/GitHub, CI/CD pipelines, DevOps practices, and infrastructure automation. Expertise in automation/configuration management tools (Terraform, Ansible, Jenkins, ArgoCD). Familiar with Spring Boot, React, TypeScript, Node.js, and package management tools (NPM, Yarn, Maven, Gradle). Support Engineering & Troubleshooting Proven experience in L1/L2/L3 support for enterprise cloud applications and infrastructure. Strong troubleshooting skills for complex distributed systems and microservices architectures. Experience with incident management tools (ServiceNow, Jira Service Management, PagerDuty). Proficiency in log analysis and monitoring tools (ELK Stack, Splunk, Datadog, CloudWatch, Grafana). Expertise in debugging production issues in containerized environments and Kubernetes clusters. Experience with APM tools (New Relic, Dynatrace, AppDynamics). Experience conducting root cause analysis and implementing corrective actions. Strong documentation skills for creating runbooks, troubleshooting guides, and knowledge base articles. AI & Machine Learning for Support Operations Familiarity with AI/ML frameworks (TensorFlow, PyTorch, scikit‑learn) with focus on operational use cases. Experience with LLM APIs (OpenAI, Azure OpenAI, AWS Bedrock) for building intelligent support tools. Knowledge of prompt engineering for creating AI‑powered support assistants and chatbots. Understanding of anomaly detection algorithms and their application to system monitoring. Experience implementing predictive analytics for incident forecasting and capacity planning. Knowledge of NLP for automated ticket classification and sentiment analysis. Understanding of vector databases and semantic search for intelligent knowledge base retrieval. Knowledge of AIOps platforms and intelligent event correlation techniques. Professional Skills Excellent problem‑solving skills and attention to detail. Strong communication skills with the ability to present technical concepts to business audiences. High knowledge of SDLC, application integration, and production support. Strong customer service orientation with focus on user satisfaction. Experience working in Agile/Scrum development environments. Strong communication skills with peers, partners, and customers. High knowledge of production support skills. Ability to communicate complex technical concepts clearly and effectively. Ability to remain calm and effective during high‑pressure situations and critical outages. Preferred Skills Cloud monitoring tools (Datadog, CloudWatch, Grafana, Kibana) and CI/CD pipeline tools (Artifactory, SonarQube, Vault, Aqua). Knowledge of SRE principles, observability best practices, and distributed tracing (Jaeger, Zipkin). Experience with chaos engineering tools (Chaos Monkey, Gremlin) and disaster recovery procedures. 2+ years implementing AI/ML solutions in production support environments. Experience building AI‑powered chatbots for IT support and service desk automation. Hands‑on experience with AIOps platforms (Moogsoft, BigPanda, Dynatrace). Experience with AI agent frameworks (LangChain, LangGraph, AutoGen) for support. Automation Knowledge of RAG architectures and Model Context Protocol (MCP) for AI integration. This position will be subject to U.S. export control requirements under the International Traffic in Arms Regulations (ITAR) and/or Export Administration Regulations (EAR) and requires either verification of U.S. Person status or obtaining any necessary export license. #J-18808-Ljbffr SupportFinity™