Sr. Gen AI Engineer

Senior GenAI Engineer

Job Purpose: The Senior GenAI Engineer will develop and deploy advanced Generative AI Products, including fine-tuning V/LLM models and implementing (Graph) RAG (Retrieval-Augmented Generation) solutions. This hands-on role requires deep technical expertise and as part of the GenAI team will implement and optimize Gen AI agents for the Global Supply Chain.

Why is this job critical? This role ensures the effective use of Generative AI technologies within a Global Supply Chain, designing robust solutions, optimizing performance, and implementing AI governance. The GenAI Engineer is key in delivering efficient, reliable, and secure AI solutions, enhancing operational efficiency and strategic decision-making.

Responsibilities: Own Technical Implementation of Gen AI Capabilities:

• Quickly prototype scenarios until UX for user testing purposes.
• Implement state-of-the-art GenAI & agents technologies and best practices.
• Develop, experiment with, and validate Gen AI applications aligning with business objectives.
• Embed automated processes (LLMOps).
• Implement scalable, secure, and cost-effective Gen AI solutions to meet current and future business needs.
• Prototype and benchmark on the AI/ML stack, LLMOps, and AgentOps frameworks.
• Troubleshoot AI application issues, working closely with infrastructure teams and application owners.

• Foster innovation within the team to support a collaborative work environment.

Collaboration:

• Identify opportunities to apply the latest advancements in Large Language Models (LLMs) and Agents.
• Work with our cross-functional team to deliver features in an iterative manner.
• Educate the organization both from IT and the business perspectives on Generative AI.

Security and Compliance:

• Ensure all AI solutions adhere to security best practices and AI governance standards.

Technical Expertise:

• Provide deep technical expertise in Generative AI technologies and tools.
• Serve as a subject matter expert for complex technical issues and provide hands-on support.

Desired Qualifications: Education and Experience:

• Higher degree (PhD preferred) in Engineering, Statistics, Data Science, Applied Mathematics, Computer Science, Physics, Bioinformatics, or related field.
• 5+ years in at least 2 AI domains: NLP, NLG, Computer Vision, Machine Learning, GenAI etc.
• Hands-on experience with fine-tuning/training LLMs and complex Graph RAG solutions (production environment).

Technical Skills:

• Extensive knowledge of cloud services and tools (Azure & Databricks preferred), ), including Azure Machine Learning, Vertex AI, AI Search, Databricks, Mosaic ML, Genie, Webapps, Azure Service Bus, Azure DevOps, Azure CLI, Azure AI services, App Insights, and Azure OpenAI.

• Extensive knowledge of LLM Python libraries: langchain, langGraph, promptflow, semantic kernel, Autogen, graphRag, promptflow
• Good software engineering background, (developing application, API, frontend integration, security best practices, experience with fastAPI, Asyncio is a plus).
• Strong experience with Gen AI model deployment and monitoring (CI/CD, Weight&Biases GitHub pipelines is a plus).
• Advanced understanding of security, compliance, and ethical considerations in AI.

Soft Skills:

• Demonstrate a combination of business focus, strong analytical and problem-solving skills, and programming knowledge to be able to quickly cycle hypotheses through the discovery phase of the project.
• Strong problem-solving abilities.
• Excellent collaboration & communication skills to report back complex findings in a clear, structured manner.

Certifications:

• Relevant certifications in AI and machine learning such as Azure AI Engineer Associate are a plus.