About the role
Key Responsibilities
- Design, develop, and deploy enterprise-grade Generative AI applications using Azure OpenAI Service, GPT models, and OpenAI APIs.
- Lead the development of AI-powered applications using Python and .NET technologies.
- Build enterprise AI assistants, chatbots, and Copilot-style solutions for business users.
- Design and implement scalable Retrieval-Augmented Generation (RAG) solutions for enterprise knowledge search and intelligent assistants.
- Develop intelligent document processing, summarization, automation, and workflow solutions.
- Build conversational AI applications using Large Language Models and foundation models.
- Work with Azure OpenAI, Azure AI Search, Azure AI Foundry, Azure Storage, and other Azure AI services.
- Design and develop backend services, APIs, and microservices using .NET/.NET Core, C#, Python, FastAPI, or Flask.
- Integrate AI capabilities with enterprise applications, web platforms, APIs, SharePoint, Microsoft Teams, and other business systems.
- Develop vector search and semantic search solutions using Azure AI Search or other vector databases.
- Build and optimize data ingestion pipelines for documents, PDFs, structured data, and enterprise knowledge repositories.
- Work with embeddings, document chunking, indexing, retrieval, reranking, and grounding mechanisms.
- Design effective prompts, system instructions, reusable prompt templates, and prompt engineering frameworks.
- Optimize LLM applications for response quality, token usage, latency, scalability, performance, and cost.
- Define and implement LLM evaluation strategies to continuously improve AI response quality and reliability.
- Implement guardrails, content filtering, hallucination control, Responsible AI practices, and secure AI application patterns.
- Design and develop REST APIs and microservices using ASP.NET Core, C#, FastAPI, Flask, or similar frameworks.
- Support secure AI solution architecture using Microsoft Entra ID, RBAC, Managed Identity, and Azure security best practices.
- Deploy and manage AI applications using Azure App Service, Azure Functions, containers, AKS, or other relevant Azure services.
- Collaborate with architects and engineering teams to define scalable AI application architecture and integration patterns.
- Conduct code reviews and establish best practices for Python, .NET, API development, and AI application engineering.
- Mentor junior developers and AI engineers and provide technical guidance on solution design and implementation.
- Monitor application reliability, AI response quality, usage patterns, performance, and production issues.
- Troubleshoot complex AI application, API, integration, and deployment issues.
- Maintain technical documentation, solution architecture documents, design standards, and reusable knowledge base articles.
- Stay updated with the latest advancements in Generative AI, LLMs, Azure AI, agentic AI, and enterprise application development.
- 5–8 years of overall experience in software application development.
- Minimum 2 years of hands-on experience in .NET/.NET Core and C# development.
- Strong hands-on experience in Python development, particularly for AI and Generative AI applications.
- Strong experience with Azure OpenAI, OpenAI APIs, GPT models, embeddings, and prompt engineering.
- Hands-on experience designing and developing RAG-based applications, semantic search, enterprise knowledge assistants, or AI-powered Copilots.
- Experience building scalable backend applications using ASP.NET Core, .NET Web APIs, REST APIs, FastAPI, Flask, or microservices architecture.
- Strong knowledge of C#, .NET/.NET Core, ASP.NET Core, Web APIs, and enterprise application development.
- Experience with AI frameworks such as LangChain, Semantic Kernel, LlamaIndex, or similar frameworks.
- Good understanding of vector search, embeddings, document chunking, indexing, retrieval, reranking, and grounding.
- Hands-on experience with Azure AI Search and other relevant Azure AI services.
- Strong knowledge of Python, C#, REST APIs, JSON, and software engineering best practices.
- Experience integrating AI capabilities into existing .NET-based or enterprise applications.
- Knowledge of databases such as SQL Server, PostgreSQL, Cosmos DB, or similar technologies.
- Experience with Azure Functions, Azure Storage, Azure App Service, Azure Kubernetes Service (AKS), or containerized deployments.
- Strong understanding of Azure DevOps, Git, CI/CD pipelines, and software release practices.
- Knowledge of secure API integration and identity management using Microsoft Entra ID, RBAC, Managed Identity, and Azure security practices.
- Good understanding of LLM evaluation, prompt optimization, guardrails, Responsible AI, and hallucination mitigation.
- Experience designing scalable, secure, and maintainable enterprise applications.
- Strong analytical, problem-solving, communication, and stakeholder management skills.
- Ability to translate complex business requirements into practical and scalable AI and software solutions.
- Experience with Microsoft Copilot Studio, Power Platform, or Microsoft 365 integration.
- Knowledge of Agentic AI and multi-agent frameworks such as AutoGen, CrewAI, or Semantic Kernel Agents.
- Experience with vector databases such as FAISS, ChromaDB, Pinecone, or Azure AI Search Vector Index.
- Experience with Azure Document Intelligence, OCR, or Intelligent Document Processing.
- Exposure to MLOps, LLMOps, AI monitoring, evaluation frameworks, and production support.
- Experience designing and implementing event-driven or distributed microservices architectures.
- Knowledge of Docker, Kubernetes, and cloud-native application development.
- Experience integrating AI solutions with enterprise platforms such as SharePoint, Microsoft Teams, ITSM platforms, ERP systems, or other business applications.
- Experience with application modernization or integrating Generative AI capabilities into existing .NET applications.
- Domain exposure in manufacturing, automotive, supply chain, quality, finance, enterprise IT, or digital transformation.
- Experience leading technical discussions, solution design sessions, and mentoring junior developers.
- Clear objectives that align your work with our mission and enable meaningful contributions.
- Abundant opportunities to engage with customers, product managers, technical leaders, architects, and leadership teams.
- Progressive career paths supported by continuous guidance and feedforward sessions from managers.
- Opportunities to build strong connections across diverse communities of interest.
- Flexibility to choose mentors who can guide your current work and future career aspirations.
- Continuous learning and upskilling opportunities through Nexversity.
- Opportunities to explore different functions, develop new skills, and work with emerging technologies.
- Hybrid work model supporting flexibility and work-life balance.
- Comprehensive family health insurance coverage.
- Accelerated career paths designed to help you achieve your professional aspirations.
Join our passionate team and tailor your growth with us!