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Join our Innovation Analytics & AI team as a GenAI Engineer IV, where you’ll shape the future of AI solutions for enterprise-scale impact. This expert-level role drives strategy, architecture, and implementation of cutting-edge Generative AI systems using LLMs (OpenAI, Gemini, Llama2, GPT-4) and multi-modal models on Azure and cloud platforms. You’ll design cloud-native architectures, build RAG workflows, and integrate structured/unstructured data to deliver secure, scalable AI solutions. Using tools like Promptflow, LangChain, Azure AI Search, and Vector DBs, you’ll create agentic AI frameworks, optimize performance, and ensure ethical compliance. You will collaborate and guide Solution Architects to align AI strategies with business goals, ensuring performance, security, and scalability while integrating structured and unstructured data into analytics platforms. As a technical leader, you’ll mentor engineers, influence enterprise AI strategy, and foster a culture of innovation and continuous learning. This role offers the chance to drive impactful AI initiatives, collaborate across teams, and stay ahead of industry trends.
Job Responsibility:
Lead the strategy, design, architecture, and implementation of scalable Generative AI solutions using LLMs (e.g., OpenAI, Gemini, Llama2, GPT-4), multi-modal models, and open-source frameworks within Azure Microsoft Infrastructure
Develop robust data integration pipelines and RAG workflows using tools like Promptflow, Azure AI Search, Semantic Search, Hybrid Search, Document Intelligence, Skillsets, Generative RAG Search, Vector DBs, Azure OAI, AI Hub, Agents, Assistants, LangChain, Hugging Face, Llama Index, and Semantic Kernel
Design and implement robust test automation strategies within CI/CD pipelines, define observability metrics using Azure Application Insights and Dynatrace, and support production deployments with detailed documentation and risk mitigation
Collaborate with Solution Architects to ensure successful delivery of enterprise initiatives such as application security, API development, architecture, and test automation
Act as a subject matter expert in tools and technologies, lead internal learning forums, set strategic objectives, and drive the adoption of innovative methods
Requirements:
4-Year / bachelor’s degree, preferably in Computer Science, Data Science, Artificial Intelligence, or equivalent experience
8+ years in AI engineering with deep expertise in GenAI and cloud architectures
Advanced skills in Python, .NET, C#, and tools like LangChain, Hugging Face
Strong knowledge of LLMs, multi-modal models, and CI/CD automation
Proven leadership in AI strategy, mentoring, and enterprise-scale delivery
Expert-level proficiency in Python, .NET, and C# programming for AI applications