Lead Data & AI Engineer

Vanguard
Malvern, PA, United States
8 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
9 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Data Architecture Information Engineering Data Governance Meta-Data Management Azure Machine Learning Software Deployment Systems Integration Workflow Management Systems Data Processing Cloud Platform System
+9 more
Multi-Agent Systems Event Driven Architecture AWS Glue Real Time Data Machine Learning Operations Virtual Agents Stream Processing Data Pipelines Databricks

Job description

  • 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.

Requirements

  • 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.

About the company

hackajob is collaborating with Vanguard to connect them with exceptional professionals for this role.

Join us in a high-impact, high-visibility role where you will pioneer world-class Data & AI engineering solutions, building the next generation of intelligent, agent-driven systems that power real-time business decisions., About Vanguard

At Vanguard, we don’t just have a mission-we’re on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients’ lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.

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