AI Specialist

• Identify AI Opportunities: Work closely with different departments to identify potential AI use cases that can solve business problems and create value.
• Use Case Development: Develop detailed AI use cases, including problem statements, objectives, expected outcomes, and success metrics.
• Feasibility Analysis: Conduct feasibility studies to assess the technical and economic viability of proposed AI use cases.
• Lead end to end technical solution design leveraging Azure Databricks, Azure OpenAI, Azure Data Lake, and other Azure services.
• Architect scalable data & AI systems including ingestion, transformation, storage, model deployment, and governance.
• Define reference architectures, best practices, and reusable solution patterns.
• Ensure solutions align with security, compliance, and enterprise governance standards.
• Design, fine tune, and optimize LLM based solutions using Azure OpenAI Studio.
• Build and demonstrate PoCs, pilots, and technical accelerators showcasing generative AI capabilities.
• Guide teams on RAG architectures, embeddings, vector databases, and enterprise LLMOps.
• Collaborate with product and engineering teams to ensure scalable, cost-efficient data solutions.
• Work closely with business leaders, architects, and engineering teams to understand requirements and define solution roadmaps.
• Provide trusted advisory on data governance, MLOps, model risk management, and LLM security.
• Conduct technical deep-dives, demos, and enablement sessions for internal/external stakeholders.
• Collaborate with cross functional teams to evaluate tooling, platforms, and product enhancements.
• Mentor technical teams on best practices in data engineering, machine learning, and cloud-native architectures.

Education and Experience Requirements:

• Education: Bachelor’s degree in computer science, AI, Classic Machine Learning models, Data Science, or a related field. Master’s degree preferred.
• Experience: 5–10 years of overall experience in Data Science, AI, Data Engineering, or Technical Architecture roles.
• Experience in data science, data engineering, or ML engineering.
• Proven experience building production-grade ML/AI systems.
• Prior exposure to LLMs, foundation models, or generative AI solutions
• 3+ years designing solutions on Azure + Databricks.
• Prior experience in a Technical Specialist, Solutions Architect, or technical consulting role preferred.

Required Knowledge and Skills:

• Solid technical background with understanding and/or hands-on experience in AI technologies.
• Strong programming skills in Python and SQL.
• Hands-on expertise with:
  • Azure OpenAI Studio (prompting, fine-tuning, deployments)
  • Azure Databricks (Spark, Delta Lake, notebooks, workflows)
  • Azure Data Lake Storage (ADLS), Azure Data Factory, Azure Functions
• Experience with MLflow, MLOps, CI/CD pipelines.
  • Solid understanding of data modeling, distributed systems, and cloud-native architectures.