Description

Build and operationalize multi-agent systems, RAG pipelines, and AI-powered privacy automation on Azure.

This role is on-site.

Responsibilities

• Design and build multi-agent systems, orchestration layers, and agentic workflows using LangChain, LangGraph, or Google ADK.
• Develop and operationalize RAG pipelines integrating LLMs (Claude, Gemini, GPT-4) into production privacy applications.
• Implement structured prompting, decision workflows, and tool orchestration, including MCP-based architectures, for autonomous agent systems.
• Build AI-powered automation for privacy operations, including intelligent DSR routing, threshold monitoring, and automated regulatory notifications.
• Deploy and manage AI workloads on Azure or AWS, ensuring scalable deployments via Docker and Kubernetes.

Required Skills

• 5+ years of experience in AI/ML engineering and production deployment.
• Proficiency with Azure Data Factory, Databricks, Snowflake, and PySpark for data pipeline optimization.
• Experience with CI/CD tools like GitLab or Azure DevOps for MLOps best practices.
• Knowledge of monitoring and alerting using Splunk, AppDynamics, or Grafana.
• Strong understanding of vector databases, embedding strategies, and prompt engineering.
• Experience implementing responsible AI principles, fairness, and compliance with privacy regulations (CCPA, CPRA).
• Bachelor's degree in Computer Science or related field.

Key Skills

Education

Bachelor's degree