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You will work across backend services, orchestration layers, and data pipelines-ensuring that AI features are reliable, scalable, and performant.\nThis is a hands-on engineering role requiring strong problem-solving, system design, and the ability to operate in fast-evolving AI environments.\nKey Responsibilities\nBuild and maintain backend services and internal tools in Python for AI-powered applications. \nIntegrate LLM APIs into production workflows, including prompt handling, response processing, validation, and retries. \nDesign and implement scalable REST APIs, async workflows, and background job systems. \nMaintain and enhance components of a multi-language codebase (C#/C++, Python, web technologies) where applicable. \nWork with structured and unstructured data to prepare inputs, transform outputs, and support downstream systems. \nDevelop systems for prompt management, model routing, response validation, and failure handling. \nDebug complex issues across backend logic, API integrations, and distributed services. \nMonitor system performance using telemetry tools and proactively identify and resolve bottlenecks. \nAutomate recurring workflows related to data processing, evaluation, and reporting. \nCollaborate with cross-functional teams to turn ambiguous product ideas into production-ready features. \nContribute to architecture decisions around scalability, performance, and safe use of AI systems. \nWrite clean, testable, and maintainable code while helping establish engineering best practices for AI systems. \nWhat You Bring\nEducation\nBachelor’s degree in Computer Science or a related field. \nExperience\n3+ years of professional experience in backend or systems engineering. \nStrong experience in Python development for production systems. \nExperience integrating LLM APIs or AI-driven services into real applications. \nProven ability to work within large codebases and collaborative environments. \nTechnical Skillset\nCore Skills\nPython (strong), backend system design, API development \nAsync workflows, job queues, and service orchestration \nDebugging across APIs, services, and data pipelines \nLanguages\nPython, C#, C/C++, JavaScript/TypeScript, SQL \nFrameworks & Libraries\n.NET Web API, ASP.NET (MVC & WebForms), Entity Framework \nReact, Bootstrap, Ajax \nTesting frameworks (xUnit or similar) \nAI / LLM Systems\nPrompt design, response parsing, and guardrails \nModel integration patterns and failure handling \nUnderstanding of LLM limitations and production constraints \nTools & Platforms\nAzure DevOps, Git, Docker, Terraform \nSQL Server or similar databases \nElastic Stack, Postman, Swagger \nAWS or Azure cloud environments \nArchitecture\nMicroservices, distributed systems, modular architectures \nOperating Systems\nWindows, Linux \nBuild Tools\nMake, Ninja (preferred) \nNice to Have\nExperience with RAG, embeddings, vector databases, or retrieval systems \nFamiliarity with agent workflows or multi-step orchestration 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