We are looking for a highly motivated AI/ML Software Engineer to join the Enterprise Agentic AI Platform team within IT. You will work closely with Business Analysts, and Engineering teams to design, develop, and deploy enterprise AI solutions that improve productivity and automate business workflows across Engineering, Operations, and Manufacturing. What you'll be doing: Design, develop, and deploy Agentic AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI orchestration frameworks. Build scalable AI services and reusable components integrated with enterprise applications such as PLM, SAP, and other business systems. Collaborate with business and IT teams to translate business requirements into AI-driven solutions. Develop secure, scalable APIs and enterprise integrations to enable intelligent workflows and automation. Improve AI solution quality, performance, and reliability through prompt engineering, evaluation, and continuous optimization. Partner with cross-functional teams throughout the Software Development Lifecycle (SDLC), from solution design through deployment and production support. What we need to see: Bachelor's or Master's degree in Computer Science, Information Technology, AI/ML, or a related field. 6+ years of software engineering experience with strong proficiency in Python and backend application development. Hands-on experience with Generative AI, LLMs, RAG, AI agents, REST APIs, and cloud-native application development. Experience integrating enterprise applications and building scalable, production-ready software solutions. Strong analytical, problem-solving, communicatio
Senior AI Engineer (Azure Generative AI)
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Job description
We're Hiring Senior AI Engineer (Generative AI Azure) Remote Immediate Joiners Preferred Salary: Up to 12 LPA We are seeking an experienced Senior AI Engineer to design, develop, and deploy enterprise-grade Generative AI solutions on Microsoft Azure. The ideal candidate will have strong expertise in Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), Azure AI Services, and modern AI engineering practices. Technical Summary • AI & LLMs: Azure OpenAI, GPT-4.x, OpenAI, Prompt Engineering, Prompt Chaining, Function Calling, Structured Outputs, Tool Calling, JSON Schema, Model Evaluation, Guardrails, Fine-tuning Concepts • Agentic AI: Multi-step Reasoning, Planning, Memory Management, Tool Orchestration, Multi-Agent Systems, Human-in-the-Loop Workflows, Reflection, Context Management, AI Observability • Frameworks: Semantic Kernel, Lan
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Jobiba Technologies
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