Principal Enterprise Data & AI Architect
Core
Define, evolve, and operationalize architecture for enterprise data platforms, AI/ML capabilities, and agentic data access to enable scalable, governed AI solutions.
Role type
Principal Enterprise Data & AI Architect
Builds
Cloud-based data platforms, AI/ML platforms, agentic data access services, semantic layers, and production-grade reference frameworks.
Domain
Financial services / Enterprise Data & AI Architecture
Deliverable
production ML models
Required skills
Enterprise data architecture, Cloud data platforms (AWS Redshift, Snowflake, Databricks, BigQuery), Operational databases (Aurora, Postgres, DynamoDB), Graph databases (Neo4J, Neptune), AI/ML platform engineering (SageMaker, Bedrock), Vector databases, Agentic AI & LLM application architecture, Data governance, AI governance, Prompt engineering, RAG, MCP-based tooling, Wealth management domain knowledge.
Preferred skills
Familiarity with Agent Harness or equivalent technologies.
Technologies
AWS Redshift, Snowflake, Databricks, Google BigQuery, Aurora, Postgres, DynamoDB, Neo4J, Neptune, AWS SageMaker, AWS Bedrock, Open Search, Agent Harness, MCP.
Responsibilities
Own architecture strategy and target-state designs for data and AI platforms; Lead data platform modernization from on-prem to cloud; Design scalable patterns for ingestion, transformation, and consumption across batch, streaming, and AI use cases; Evolve agentic data-access architecture to production-grade; Drive architecture reviews and define non-functional requirements; Mentor engineers and delivery teams on architecture patterns and standards.
Seniority
Principal, hands-on IC with strategy & mentorship
