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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal AI Data Architect - **Company:** GE Vernova - **Location:** Niskayuna, NY, United States - **Experience:** Expert - **Salary:** $137,700.0 - $229,600.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Information Systems, Computer Engineering, Data Architecture, Information Engineering, Data Governance, Data Security, Python (Programming Language), Machine Learning, Metadata, Role-Based Access Control, SQL Databases, Technical Data Management Systems, Enterprise Search, Enterprise Data Management, Data Processing, Data Ingestion, Large Language Models, Snowflake, AI Platforms, Kubernetes, Information Technology, Apache Kafka, Machine Learning Operations, Network Server, Data Pipelines, Serverless Computing, Amazon Redshift, Databricks - **Published:** September 24, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=173ca40d04445d1a ## About the Role * 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., * Must be willing to work out of an office located in Niskayuna, NY or Cambridge, MA., * 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 ## Description 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., * 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 ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Got AI ideas but no money? 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