# AI Engineer - Generative AI Solutions
## Key Responsibilities
### Model Development and Deployment
- Evaluate and select appropriate Generative AI models based on business needs, ensuring alignment with use case requirements
- Leverage Azure ML, OpenAI APIs, and other Generative AI technologies based on a given design
- Implement best practices for model development, training, and deployment pipelines
- Create and deploy pipelines for model training, evaluation, and monitoring in Azure ML
- Optimize model performance for latency, scalability, and accuracy, ensuring compliance with regulatory and organizational standards
### AI Integration and Innovation
- Integrate Generative AI solutions with enterprise applications, APIs, and data sources
- Leverage Azure AI model catalog (Microsoft, OpenAI, Mistral, Meta, etc) APIs to implement conversational AI, document summarization, image generation, or other innovative use cases
- Explore advancements in AI/ML technologies, recommending tools, frameworks, and practices to enhance the organization's AI capabilities
### Collaboration and Leadership
- Partner with cross-functional teams, including data engineers, cloud architects, and business analysts, to align AI/ML solutions with business objectives
- Communicate complex (Gen) AI concepts to non-technical stakeholders, fostering a culture of innovation and understanding
## Technical Requirements
- Experience delivering GenAI (LLMs) solutions, preferably on Azure
- Familiar with using Azure AI library APIs (e.g., GPT, Codex, DALLE) & other frameworks (e.g. Databricks Mosaic) to integrate Generative AI into business workflows
- Proficient with at least one programming language, such as Python, PySpark, R, SQL, etc.
- Knowledge of big data technologies (e.g., Spark, Databricks), TensorFlow, PyTorch are a plus
- Knowledge of Azure Cloud services (e.g., Azure AI Platform, Azure Data Factory, Azure Synapse, Azure Cognitive Services) and their integration with ML workflows is a plus
- Knowledge of security best practices for AI solutions, including data encryption, access control, and endpoint protection is a plus
## Soft Skills
- Excellent problem-solving and analytical thinking skills
- Strong communication and presentation skills, with the ability to translate technical concepts into business outcomes
- Proven ability to manage multiple stakeholders and prioritize tasks in a fast-paced environment
## Preferred Qualifications
- Experience with GenAI Large Language Models (LLMs) solution development and fine-tuning for domain-specific tasks
- Certifications in Azure or Databricks (e.g., Azure AI Engineer Associate, Azure Solutions Architect Expert, Databricks ML Professional, Databricks Data Engineer Professional)
- Familiarity with AI ethics, bias mitigation, and explainability techniques
- Prior experience in implementing AI/ML solutions in industries such as healthcare, finance, or retail is a plus