Principal AI Engineer

Duties & Responsibilities

• Architect and oversee end-to-end AI/ML platforms, including GenAI, LLMs, agentic workflows, and MLOps/LLMOps infrastructure.
• Lead the design and deployment of enterprise-grade GenAI applications, integrating advanced models (e.g., GPT-4, LLaMA, multimodal AI) for complex business use cases.
• Set technical standards for model selection, fine-tuning, evaluation, and responsible AI governance across teams.
• Drive adoption of best practices in data engineering, feature pipelines, and production AI using Databricks, Azure AI, Snowflake, Spark, Airflow, and related technologies.
• Champion Human-in-the-Loop (HITL) validation, feedback loops, and continuous improvement for production AI systems.
• Mentor and coach Lead/Staff AI Engineers, fostering technical excellence and career growth.
• Collaborate with cross-functional leaders (Product, Data, Engineering, Business) to define AI strategy, roadmap, and KPIs.
• Oversee AI observability, monitoring, and guardrail management using Unity Catalog, Azure AI Guardrails, OpenTelemetry, and similar tools.
• Represent the organization in external forums, conferences, and vendor engagements as a thought leader in AI/ML.

Requirements

Basic Qualifications

• Experience working in agile, cross-functional teams and delivering measurable impact.
• Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• 11+ years as over all work experience in IT industry and 8+ years of experience architecting and deploying enterprise-scale AI/ML platforms, including GenAI, LLMs, agentic architectures, and MLOps/LLMOps.
• Proven expertise in designing, implementing, and scaling AI infrastructure using Databricks, Azure AI, Snowflake, Spark, Airflow, and related technologies.
• Hands-on experience with production‑grade model selection, fine‑tuning, evaluation, and responsible AI governance.
• Strong programming skills in Python, PySpark, SQL, and experience with modern AI/ML frameworks (e.g., LangChain, Hugging Face, OpenAI Agents SDK).
• Demonstrated ability to lead cross‑functional teams and deliver measurable business impact through AI‑driven solutions.
• Experience integrating GenAI models into enterprise applications with Human-in-the-Loop (HITL) validation and feedback loops.
• Familiarity with multi‑modal AI (text, image, audio) and unstructured data processing.

Preferred Qualifications

• Experience architecting and operating large‑scale AI platforms in cloud environments (Databricks, Azure AI Foundry, Vertex AI).
• Deep knowledge of agentic frameworks (LangGraph, Databricks Genie, Azure AI Agent Orchestration) and orchestration of autonomous AI workflows.
• Advanced proficiency in MLOps/LLMOps/AgentOps tools: MLflow, ONNX, DVC, Unity Catalog, CI/CD pipelines.
• Expertise in data engineering: DBT, Spark, Lakehouse, Azure Data Factory, Snowflake.
• Strong background in observability, governance, and guardrail management: OpenTelemetry, Databricks AI Gateway, Azure Guardrails.
• Publications, patents, or conference presentations in AI/ML or platform architecture.
• Experience with regulatory compliance, responsible AI practices, and enterprise security.
• Proven track record of mentoring and developing technical talent.
• Experience with global teams and multi‑region deployments.