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# Senior Software Engineer

- **Company:** BrickRed Systems
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Application Performance Management, Automation of Tests, Microsoft Azure, C Sharp (Programming Language), Cloud Computing, Profiling, Code Review, Continuous Integration, Software Debugging, DevOps, Distributed Systems, Fault Tolerance, Python (Programming Language), Log Analysis, NoSQL, Performance Tuning, Software Deployment, SQL Databases, Data Streaming, Cloud Monitoring, LangChain, Retrieval-Augmented Generation, Large Language Models, Concurrency, Reliability of Systems, Generative AI, Backend, Agentic-AI, Event Driven Architecture, Kubernetes, Deployment Automation, AutoGen, Semantic Kernel, Dynatrace, Serverless Computing
- **Published:** November 6, 2026
- **Apply:** https://www.juju.com/job/2_173708491

## About the Role

We are seeking a Senior Software Engineer with strong hands-on experience building, operating, and maintaining large-scale production systems. The ideal candidate will have deep expertise in Python, Azure cloud services, distributed systems, and production AI applications.

This role requires engineers with genuine production ownership, on-call experience, and the ability to troubleshoot complex live incidents. Candidates should have experience building reliable, scalable backend services and maintaining AI-powered systems in real-world production environments. This is a hands-on engineering role focused on production stability, technical ownership, and engineering excellence rather than research or proof-of-concept development., * Minimum 8-10+ years of professional backend or distributed systems engineering experience.

 * Strong hands-on expertise in Python, including performance optimization, concurrency, debugging, and production reliability.
 * Proven experience building, deploying, and supporting Azure-based production systems.
 * Hands-on experience with Azure Functions, Durable Functions, Event Grid, and Service Bus.
 * Strong understanding of distributed systems, event-driven architectures, scalability, fault tolerance, and operational recovery.
 * Experience owning and resolving live production incidents, including root cause identification, remediation, validation, and preventive measures.
 * Strong troubleshooting and debugging skills across complex production environments.
 * Experience with CI/CD pipelines, automated testing, deployment strategies, and rollback mechanisms.
 * Ability to demonstrate end-to-end ownership of production applications and services., * Experience building, deploying, and maintaining production Generative AI, LLM, and RAG applications.
 * Hands-on experience with agentic AI workflows and orchestration frameworks such as LangChain, AutoGen, and Semantic Kernel.
 * Experience with high-concurrency distributed systems, queue-backed architectures, streaming platforms, and large-scale SQL/NoSQL workloads.
 * Experience managing production AI challenges, including prompt drift, latency optimization, evaluation degradation, and cost management.
 * Working knowledge of C# and experience contributing to polyglot technology environments.
 * Strong understanding of DevOps practices, observability, incident management, and production deployment automation., * Candidates must have genuine hands-on production engineering experience, not just POCs, prototypes, or research exposure.
 * Practical on-call experience and ownership of live production incidents are essential.
 * Candidates must be comfortable attending initial in-person interviews.
 * Hybrid work arrangement requires 3 days per week in the Manhattan, NYC office. Seattle-based candidates are also being considered; office arrangements should be confirmed.
 * Comprehensive background and professional experience verification will be conducted.

## Description

* Design, develop, and maintain production-grade Python services, ensuring scalability, reliability, performance, and operational stability.
 * Build and operate Azure-native distributed systems using Azure Functions, Durable Functions, Event Grid, Service Bus, and supporting cloud infrastructure.
 * Develop and maintain production-ready AI solutions, including RAG pipelines, agentic workflows, and LLM orchestration frameworks.
 * Work with AI frameworks such as LangChain, AutoGen, and Semantic Kernel.
 * Diagnose and resolve production incidents using distributed tracing, log analytics, profilers, Azure Monitor, and Application Insights.
 * Troubleshoot performance bottlenecks, cold-start latency, distributed failures, event-ordering issues, and scaling challenges.
 * Establish engineering best practices around code reviews, CI/CD, automated testing, deployment safety, and rollback strategies.
 * Own production incident investigation, root cause analysis (RCA), remediation, and post-mortem activities.
 * Contribute to secondary technology stacks, including C#, when required.
 * Drive continuous improvements in system reliability, observability, operational automation, and engineering quality.