Principal AI Data Architect

GE Vernova

2d•$137,700 - $229,600•Hybrid

About The Position

As a Principal AI Data Architect, you will define and evolve the enterprise data architecture needed to deliver trusted, scalable, secure, and cost-efficient AI products. This work starts with data. You will design systems that connect diverse data sources to AI agents and ensure the information is clean, accessible, and ready for advanced analytics. You will also shape the technical data engineering strategy, set clear architectural standards, and translate complex business priorities into robust, production-ready capabilities. You’ll partner with product managers, AI engineers, and security teams to ensure data governance, security protocols and compliance rules are enforced when Agents need access to data sources. Expect to drive strategy, provide leadership in data engineering, clarify outcomes, and shape standards. If you’re unsure, apply.

Requirements

Bachelor’s degree in computer science, Computer Engineering, Data Science or Information Systems or related field
10+ years of experience as a Data Architect, Data Engineer, ML Ops or similar role with enterprise data systems
Demonstrated ability to lead complex technical decisions and influence senior stakeholders, with strong communication skills and experience establishing data governance, security, privacy, quality, lineage, and operational standards in enterprise or regulated environments.
Demonstrated experience delivering data foundations for AI/ML or GenAI solutions, including one or more of RAG, vector databases, enterprise search, LLM evaluation, agentic workflows, feature/data pipelines, and model-serving integration
Proficiency in Python and SQL, with experience in data processing libraries
Hands on experience with MCP Servers and MCP Registries.

Nice To Haves

Experience developing on AWS Bedrock
Deep hands-on proficiency in SQL and Python, plus practical experience with data-processing and orchestration technologies such as Databricks, RedShift, Snowflake, Kafka, Airflow, or equivalent cloud-native services.
Experience with Ontologies and Semantic systems

Responsibilities

Enable AI and GenAI use cases: Ensure data is usable for LLM and ML applications, such as RAG, vector-based knowledge retrieval, agentic workflows, AI-assisted reporting, or secure data access for agents
Establish data trust, security, and responsible-AI controls including data quality and validation, lineage, metadata, privacy, RBAC/ABAC, auditability, retention, policy enforcement, and AI-output evaluation and monitoring.
Drive technology, platform, and investment decisions by evaluating cloud data services, AI platforms, frameworks, and vendors; lead build-versus-buy assessments with explicit consideration of performance, resilience, security, operability, and total cost of ownership.
Define the target-state AI data architecture and multi-year roadmap for data ingestion, integration, storage, modeling, semantic access, and AI consumption; establish reusable reference architectures and engineering standards across domains.
Provide principal-level technical leadership across the organization by leading architecture reviews, resolving complex cross-domain design issues, partnering with product, engineering, security, and executive leaders

Benefits

medical
dental
vision
prescription drug coverage
Health Coach from GE Vernova, a 24/7 nurse-based resource
Employee Assistance Program, providing 24/7 confidential assessment, counseling and referral services
GE Vernova Retirement Savings Plan, a tax-advantaged 401(k) savings opportunity with company matching contributions and company retirement contributions
access to Fidelity resources and financial planning consultants
tuition assistance
adoption assistance
paid parental leave
disability benefits
life insurance
12 paid holidays
permissive time off
Relocation Assistance Provided