Responsibilities:
Own Technical Implementation of Gen AI Capabilities:
- Quickly prototype scenarios till UX for user testing purposes
- Implement state-of-the-art GenAI & Agents technologies and best practices.
- Develop, experiment and validate Gen AI applications aligning with business objectives
- Embed automated processes (LLMOps)
- Design scalable, secure, and cost-effective Gen AI solutions to meet current and future business needs.
- Influence the AI/ML stack, LLMOps and AgentOps frameworks
- Lead troubleshooting of AI application issues, working closely with infrastructure teams and application owners.
Leadership and Team Management:
- Lead internal and external developers to deliver on the Generative AI roadmap, providing technical guidance.
- Lead discussions and use quantitative skills to positively influence decision making
- Foster innovation within the team to support a collaborative work environment
- Contribute to talent development and continuous learning opportunities within the team.
Collaboration and Stakeholder Management:
- Identify opportunities to apply the latest advancements in Large Language Models (LLMs) and Agents
- Work with our cross-functional team to define and deliver features in an iterative manner.
- Work closely with application owners, business units, and other stakeholders to understand requirements and translate them into effective AI solutions.
- Facilitate collaboration between teams to troubleshoot and resolve complex issues.
- 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
- Total 15+ years of experience and 5+ years in at least 2 AI domains: NLP, NLG, Computer Vision, Machine Learning, etc.
- Hands-on experience with LLMs fine-tuning/training
- Fluency in English
Technical Skills:
- Extensive knowledge of cloud services and tools (Azure 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
- 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 hypothesis through the discovery phase of the project
- Excellent leadership, communication, and collaboration skills.
- Strong problem-solving and decision-making abilities.
- Ability to manage multiple projects and priorities in a dynamic environment.
- Proven track record of driving innovation and continuous improvement.
- Excellent written and communications 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.