AI Engineer (.Net, Kafka)

Required experienced AI Expert Engineer with experience of software engineering and strong expertise in .NET technologies, Kafka-based event-driven architectures, AI/ML solution development, and cloud-native platforms. The ideal candidate will be responsible for designing, developing, and deploying enterprise-scale intelligent applications that leverage Generative AI, machine learning, distributed systems, and Real Time data processing.Candidate will collaborate with cross-functional teams to build scalable AI-powered solutions, drive innovation, and establish best practices for modern software architecture, integration, and automation.

Your responsibilities: Design and develop enterprise-grade AI solutions using .NET technologies and modern AI frameworks. Build scalable, event-driven microservices architectures utilizing Apache Kafka for Real Time data streaming and processing. Integrate Generative AI, Large Language Models (LLMs), NLP, and machine learning capabilities into business applications. Develop RESTful APIs, Back End services, and reusable components using .NET Core/.NET 8 and C#. Design and implement Retrieval-Augmented Generation (RAG) architectures and AI orchestration frameworks. Collaborate with data scientists, architects, product owners, and business stakeholders to translate business requirements into AI-driven solutions. Optimize AI pipelines, inference workloads, and streaming applications for performance, scalability, and reliability. Implement secure, resilient, and highly available cloud-native applications on Azure or AWS. Establish CI/CD pipelines and DevOps practices for automated deployment and monitoring. Guide technical teams in architecture decisions, code reviews, engineering standards, and AI best practices.

Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, or a related field. Hands-on experience in software engineering and enterprise application development. Proven experience delivering large-scale distributed systems and cloud-based applications. Strong expertise in C#, .NET Core/.NET Framework, ASP.NET Core, and Microservices Architecture. Demonstrated experience implementing AI/ML and Generative AI solutions in enterprise environments. Strong knowledge of software design patterns, clean architecture, and domain-driven design principles. Experience working in Agile/Scrum delivery environments. Excellent analytical, problem-solving, communication, and stakeholder management skills. Ability to lead technical discussions, architecture reviews, and solution design workshops. Experience working with globally distributed teams and complex enterprise ecosystems. Monitor production environments and troubleshoot complex issues across distributed systems. Ensure compliance with enterprise security, governance, and responsible AI practices. Evaluate emerging AI technologies and recommend innovative solutions to improve business outcomes. Mentor junior and senior engineers and contribute to technical capability development across the organization.

Desirable skills/knowledge/experience: AI & Generative AI Hands-on experience with OpenAI, Azure OpenAI, Anthropic Claude, Gemini, or similar LLM platforms. Experience building RAG solutions using vector databases. Knowledge of prompt engineering, AI agents, autonomous workflows, and conversational AI. Familiarity with LangChain, Semantic Kernel, AutoGen, LangGraph, or equivalent orchestration frameworks. Experience with AI observability, model evaluation, and responsible AI practices. Understanding of machine learning life cycle (MLOps) and model deployment strategies.

.NET Technologies Expert-level proficiency in C#, ASP.NET Core, .NET 6/7/8. Experience with Entity Framework Core, LINQ, Dependency Injection, and Web APIs. Strong understanding of Multithreading, asynchronous programming, and performance optimization. Experience with gRPC, GraphQL, and distributed application design patterns.

Kafka & Event Streaming Extensive experience with Apache Kafka, Kafka Streams, Kafka Connect, and Schema Registry. Expertise in designing event-driven and asynchronous architectures. Knowledge of message serialization formats such as Avro, JSON, and Protobuf. Experience implementing fault-tolerant, high-throughput, low-latency streaming systems. Hands-on experience with event sourcing and CQRS patterns.