AVP, AI Data Engineering, Customer Data Ecosystem
Hartford CT- Home Office, United States
USD 182K-273K Executive-level Full Time
Tasks
- Build AI data pipelines for structured and unstructured data
- Build and mentor data engineering and architecture team
- Collaborate with technology and AI teams using agile at scale
- Define data governance and data quality frameworks
- Define ontologies and knowledge graphs
- Deploy semantic and knowledge platforms with governance and security
- Design real-time data streaming pipelines
- Design semantic layers for business meaning
- Enable semantic first AI for LLM and agent consumption
- Ensure data architecture alignment with enterprise standards
- Establish AI data engineering best practices for quality and compliance
- Evangelize agentic data engineering patterns and playbooks
- Implement AI driven productivity improvements for data lifecycle
- Lead data and analytics portfolio strategy
- Lead proof of concepts for agentic AI technologies
- Manage portfolio budget and financials
Perks/Benefits
Skills/Tech-stack
AWS Lambda | Agent SDK | Amazon EC2 | Amazon S3 | Data APIs | Data Architecture | Data Engineering | Data Governance | Data Pipelines | Data Quality | Data Streaming | Data integration | Google Agent SDK | Knowledge graphs | LLM optimization | Langchain | Langgraph | Language Models | Large Language Models | MCP | Ontology Modeling | OpenSearch | Pinecone | Postgres | Prompt engineering | RAG | Real Time | Real-Time Data Streaming | Real-time Data | Retrieval-Augmented Generation | Semantic layers | Snowflake | Vector Databases | Vertex AI
Education
Regions
Countries
States
Cities
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