AI Engineer II

Duties & Responsibilities

• Translate business requirements into scalable and well-documented AI/ML pipelines using Databricks, Azure AI, and Snowflake.
• Design and deploy GenAI-powered applications using pretrained models (e.g., GPT-4, LLaMA) for tasks such as text generation, summarization, code synthesis, and personalization.
• Build and orchestrate agentic AI workflows using frameworks like LangChain, OpenAI Agents SDK, and Databricks Genie, enabling autonomous task execution and multi-agent collaboration.
• Integrate GenAI models into enterprise applications with Human-in-the-Loop (HITL) validation and feedback loops for production readiness.
• Conduct model selection, fine-tuning, and evaluation using MLflow, ONNX, and custom batch testing frameworks.
• Develop and maintain data pipelines for feature engineering, model training, and inference using DBT, Spark, Airflow, and Azure Data Factory.
• Monitor and troubleshoot production deployments, addressing model drift, latency, and data quality issues.
• Ensure responsible AI operations through governance, observability, and guardrail management using Unity Catalog, Azure AI Guardrails, and OpenTelemetry.

Preferred Qualifications

• Languages: Python, PySpark, SQL
• GenAI & LLM Tools: LangChain, LlamaIndex, Hugging Face Transformers, OpenAI Agents SDK, Gemini, LoRA
• Agentic Frameworks: LangGraph, Databricks Genie, Azure AI Agent Orchestration
• MLOps/LLMOps/AgentOps: MLflow, ONNX, DVC, Unity Catalog, CI/CD pipelines
• Data Engineering: DBT, Spark, Lakehouse, Azure Data Factory, Snowflake
• Observability & Governance: OpenTelemetry, Databricks AI Gateway, Azure Guardrails