Senior Lead Data & AI Engineer

Vanguard Group, Inc.

$120K — $150K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 9-12+ years in data engineering with a focus on AI in cloud environments (Databricks, AWS)
  • Experience with deploying AI agents using frameworks like RAG and AgentOps
  • Proficient in AWS AI/ML services such as SageMaker and Bedrock
  • Strong understanding of lakehouse architecture and metadata management
  • Expertise in data orchestration and scalable AI workflows

Responsibilities

  • Design and build reusable, metadata-driven data frameworks for AI workflows
  • Implement Delta Live Tables and Lakeflow jobs for automated data processing
  • Use Databricks Workflows for scheduling and monitoring AI deployments
  • Integrate real-time data processing with Lakeflow for AI agents
  • Ensure orchestration between AI models and data pipelines using event-driven architectures
  • Deploy and manage AI agents with frameworks like AgentOps and Agent-bricks
  • Maintain AI agent lifecycles and scaling using tools like SageMaker

Benefits

  • Professional development opportunities
  • Access to cutting-edge technologies
  • Collaborative work environment
  • Focus on innovation and scalability
Full Job Description
Key Responsibilities:
  • Architect and build reusable, metadata-driven data and AI engineering frameworks that standardize ingestion, transformation, feature engineering, and AI workflow deployment. Leverage Databricks, lakehouse architecture, declarative pipelines, and cloud-native services to enable scalable, governed, and reusable data products across the organization.
  • Architect and deploy Delta Live Tables and Lakeflow jobs on Databricks to automate data processing, AI pipelines, and agent data refresh cycles.
  • Leverage Databricks Workflows and Job Orchestration to schedule and monitor AI agent deployments across multiple business workflows.
  • Integrate Lakeflow for real-time data stream processing, ensuring AI agents are updated and responsive to live data.
  • Ensure seamless orchestration between AI models and data pipelines, using event-driven architectures for real-time inference and deployment.
  • Implement and orchestrate AI agents using frameworks such as Agentic systems, AgentOps tooling, and solutions like Agents on Databricks (Agent-bricks).
  • Hands-on experience deploying AI agents using RAG, Graph RAG, MCP-enabled integrations, and agent orchestration frameworks such as AgentOps, AgentBricks, LangGraph, or cloud-native orchestration services.
  • Manage AI agent lifecycles, monitoring, and scaling using tools like SageMaker, Bedrock, or AI orchestration frameworks on AWS.
  • Ensure robust data governance, metadata management, and AI observability through Unity Catalog, AWS Glue, or custom metadata layers.
  • Design for scalability and modularity, ensuring AI agents are reusable across multiple business processes.


Qualifications:
  • 9-12+ years in data engineering, specializing in AI deployment within cloud ecosystems (Databricks, AWS).
  • Hands-on experience deploying AI agents using frameworks like RAG, graph RAG, and orchestrating agents (AgentOps, Agent-bricks, etc.).
  • Proficient in AWS AI/ML services (SageMaker, Bedrock) and orchestration tools (MWAA, Step Functions).
  • Strong knowledge of lakehouse architecture, Unity Catalog, and data modeling best practices.
  • Deep experience in data orchestration, monitoring, and scalable AI-driven workflows.

Special Factors

Sponsorship
Vanguard is not offering visa sponsorship for this position.

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