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# Sr Software Engineer I

- **Company:** RWE Americas
- **Location:** Austin, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** .NET Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Advanced Message Queuing Protocol, Microsoft Azure, C Sharp (Programming Language), Cloud Computing, Program Optimization, Code Reuse, Code Review, Continuous Integration, Extract Transform Load (ETL), DevOps, Distributed Systems, Python (Programming Language), Machine Learning, Performance Tuning, Prometheus, Azure DevOps Pipelines, Standard Sql, Software Engineering, TypeScript, Software Vulnerability Management, WebSocket, Automated Data Processing (ADP), Data Logging, Data Classification, Cloud Monitoring, ReactJS, Delivery Pipeline, Large Language Models, Grafana, Kubernetes Helm Charts, Reliability of Systems, Kubernetes, Information Technology, Deployment Automation, Restful APIs, Terraform, Golang, Microservices
- **Published:** August 30, 2026
- **Apply:** https://dejobs.org/x/x/B548BE4DC0144191833A14A3D90F3932/job/

## About the Role

* Education Credentials: Bachelor's degree in Computer Science, Software Engineering, IT, or related fields-or equivalent proven track record of software engineering excellence in complex systems
 * Production Experience: 5+ years of verified software engineering experience handling end-to-end production scale, service isolation, and lifecycle management within distributed, cloud-native enterprise environments
 * Multi-Language Polyglot Profile: High production proficiency across C#/.NET, Python, and TypeScript/React stacks, supplemented by a practical working familiarity with Go and robust relational/non-relational SQL database operations
 * Cloud Infrastructure & DevOps: Hands-on engineering depth managing Azure cloud environments, production container orchestration (Kubernetes/AKS), Infrastructure-as-Code (Terraform/Helm charts), and declarative CI/CD release pipelines via Azure DevOps
 * Advanced Data Workflows: Direct hands-on background constructing and managing automated high-volume ETL data jobs, utilizing workflow management schedulers like Apache Airflow.
 * AI/ML Framework Integration (Preferred): Practical familiarity deploying, querying, or connecting to downstream data science models, statistical predictive analytics modules, or modern LLM APIs to drive automated multi-variable data classification
 * Complex Domain Exposure (Preferred): Prior domain familiarity operating within energy trading, electrical utilities, industrial automation IoT, or equivalent continuous streaming big data platforms

## Description

* Distributed Architecture: Lead the end-to-end system design, robust implementation, and production scale of secure, event-driven microservices across Azure cloud environments
 * Intelligent Automation & AI: Build and mature automated data processing flows, intentionally integrating Machine Learning (ML) anomaly detection models to systematically track, evaluate, and categorize industrial asset downtime
 * High-Throughput ETL Pipelines: Architect and scale resilient background ingestion engines and low-latency APIs (REST, WebSockets, AMQP protocols) capable of processing non-stop, continuous, high-volume operational telemetry data flows
 * Technical Anchor & Leadership: Translate sophisticated business use cases directly into executable technical blueprints. Conduct comprehensive multi-language code reviews (C#/.NET, Python, TypeScript, Go) to optimize security, code reuse, and overall system reliability
 * Proactive Observability: Establish comprehensive monitoring, distributed logging, and real-time alerting systems (utilizing Prometheus, Grafana, and Azure Monitor) to build deep operational insight and radically minimize unplanned production downtime
 * Technical Documentation: Architect comprehensive system design documents and technical blueprints, accelerating team velocity, streamlining developer onboarding, and ensuring operational readiness
 * Performance & Security: Drive proactive security audits and performance tuning, establishing automated vulnerability remediation and code optimization frameworks across the platform
 * Incident Resolution: Lead root-cause analysis for high-priority production incidents, collaborating across engineering teams to implement permanent preventative engineering fixes
 * CI/CD & DevOps: Modernize Azure DevOps CI/CD pipelines to maximize deployment automation, accelerate release velocity, and improve developer efficiency


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