Senior Software Engineer

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., n \n

• Design, develop, and maintain production-grade Python services, ensuring scalability, reliability, performance, and operational stability. \n

• Build and operate Azure-native distributed systems using Azure Functions, Durable Functions, Event Grid, Service Bus, and supporting cloud infrastructure. \n

• Develop and maintain production-ready AI solutions, including RAG pipelines, agentic workflows, and LLM orchestration frameworks. \n

• Work with AI frameworks such as LangChain, AutoGen, and Semantic Kernel. \n

• Diagnose and resolve production incidents using distributed tracing, log analytics, profilers, Azure Monitor, and Application Insights. \n

• Troubleshoot performance bottlenecks, cold-start latency, distributed failures, event-ordering issues, and scaling challenges. \n

• Establish engineering best practices around code reviews, CI/CD, automated testing, deployment safety, and rollback strategies. \n

• Own production incident investigation, root cause analysis (RCA), remediation, and post-mortem activities. \n

• Contribute to secondary technology stacks, including C#, when required. \n

• Drive continuous improvements in system reliability, observability, operational automation, and engineering quality. \n

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. \n

• Strong hands-on expertise in Python, including performance optimization, concurrency, debugging, and production reliability. \n

• Proven experience building, deploying, and supporting Azure-based production systems. \n

• Hands-on experience with Azure Functions, Durable Functions, Event Grid, and Service Bus. \n

• Strong understanding of distributed systems, event-driven architectures, scalability, fault tolerance, and operational recovery. \n

• Experience owning and resolving live production incidents, including root cause identification, remediation, validation, and preventive measures. \n

• Strong troubleshooting and debugging skills across complex production environments. \n

• Experience with CI/CD pipelines, automated testing, deployment strategies, and rollback mechanisms. \n

• Ability to demonstrate end-to-end ownership of production applications and services. \n, * Hands-on experience with agentic AI workflows and orchestration frameworks such as LangChain, AutoGen, and Semantic Kernel. \n

• Experience with high-concurrency distributed systems, queue-backed architectures, streaming platforms, and large-scale SQL/NoSQL workloads. \n

• Experience managing production AI challenges, including prompt drift, latency optimization, evaluation degradation, and cost management. \n

• Working knowledge of C# and experience contributing to polyglot technology environments. \n

• Strong understanding of DevOps practices, observability, incident management, and production deployment automation. \n, * Candidates must have genuine hands-on production engineering experience, not just POCs, prototypes, or research exposure. \n

• Practical on-call experience and ownership of live production incidents are essential. \n

• Candidates must be comfortable attending initial in-person interviews. \n