AI Engineer (Manager level)

Qualifications

• 6-7 years total (at least 3 years in all technologies listed below)
• Azure AI Ecosystem: AI Services, GPT models, vector search, Cognitive search, Document Intelligence, Azure queues
• Advanced Python proficiency (including multithreading, document processing, packaging)
• Theoretical understanding of LLM driven applications
• Experience with deep learning and Natural Language Processing (NLP)
• Hands-on experience with using and configuring Azure OpenAI language models
• Strong software engineering skills (high code quality, debugging, Azure CI/CD)
• Experience with load testing of generative AI applications
• Solid understanding of Machine Learning
• Hands-on experience with data exploration and building machine learning models
• Document code and document detailed designs
• Excellent problem solving and troubleshooting skills
• Experience in working with Databricks and Spark
• BSc or greater in Data Science, Computer Science, Math or Statistics
• Highly developed written communication skills and capable of producing global and sensitive communications to a varied audience at all levels in both Practice Areas and Business Services.
• Excellent verbal and interpersonal communications skills – some form of customer-facing interaction or consulting experience is a plus.
• Makes decisions that solve the immediate problem and prevent it from occurring again.
• Prepares for potential problems and contingencies in case things go wrong.
• Takes prompt action to resolve problems quickly.
• Makes pragmatic and practical decisions about how centrally driven initiatives should be implemented locally.
• Uses all relevant sources of information, including the team and other colleagues, to generate solutions.
• Takes account of different needs and concerns in order to effectively communicate with others.
• Communicates effectively with the team through structured meetings and reviews.
• Resolves conflict and delivers feedback in an assertive and transparent way.
• Remains positive even if progress is slow and solutions are diluted.
• Is open to learning new skills.
• Demonstrates a drive towards continual personal growth and development.
• Learn about and champion best practices in code, architecture & processes.
• Contribute to the architecture and development direction of the team to ensure quality code is written and excellent products are built