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Advisor - Data Trust & AI Products

Job in Houston, Harris County, Texas, 77246, USA
Listing for: PVH (Tommy Hilfiger/Calvin Klein)
Full Time position
Listed on 2026-07-21
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 180000 - 260000 USD Yearly USD 180000.00 260000.00 YEAR
Job Description & How to Apply Below

Advisor - Data Trust & AI Products

Oxy is seeking a unique technical leader who thrives at the intersection of Data Quality, Data Governance, AI Development, and Product Innovation. This highly visible role will spend approximately 50% of its time driving enterprise data quality and data trust initiatives and 50% building AI-powered products, copilots, intelligent agents, and data-driven solutions that create measurable business value.

Job Summary

Are you passionate about building AI-powered products that transform the way people work while ensuring the data behind them is trusted, protected, and business-ready? You will play a critical role in shaping Oxy's AI future by ensuring our data is trusted, protected, and AI-ready while simultaneously developing innovative products that leverage that foundation.

What You'll Work On
  • Establish and lead enterprise data quality measurement across structured data domains.
  • Define data quality KPIs, scorecards, and executive dashboards.
  • Implement automated monitoring and controls for completeness, accuracy, consistency, and timeliness.
  • Drive enterprise data classification, protection, and governance initiatives.
  • Partner with business leaders and data owners to improve data quality and accountability.
  • Enable trusted, governed, and AI-ready data assets across the enterprise.
  • Support metadata, lineage, stewardship, and data catalog initiatives.
  • Design, build, and deploy AI-powered applications, copilots, intelligent agents, and business solutions.
  • Partner directly with business teams to identify opportunities where AI can drive measurable value.
  • Develop GenAI solutions leveraging LLMs, RAG architectures, enterprise knowledge bases, and agentic workflows.
  • Build prototypes, MVPs, and production-ready AI products that solve real business problems.
  • Integrate enterprise data sources into AI applications while ensuring governance and security requirements are met.
  • Evaluate emerging AI technologies and drive innovation across the enterprise.
  • Translate business challenges into scalable AI products and solutions.
Required Qualifications
  • 10+ years of experience in Data Management, Data Engineering, Data Governance, AI Development, or Product Engineering.
  • Strong expertise in SQL, Python, and cloud-native development.
  • Hands‑on experience with Databricks & AWS.
  • Experience developing AI solutions using LLMs, RAG, vector databases, AI agents, or enterprise AI platforms.
  • Strong understanding of enterprise data quality, governance, metadata, and data protection.
  • Experience delivering products from concept through deployment and adoption.
  • Ability to work directly with business stakeholders to identify opportunities and rapidly build solutions.
  • Experience with CI/CD pipelines, Azure Dev Ops, Git Hub, or equivalent development platforms.
  • Experience deploying AI applications in cloud environments including AWS and Azure.
  • Understanding of MLOps practices including model lifecycle management, monitoring, observability, and performance optimization.
  • Experience implementing logging, monitoring, telemetry, and usage analytics for AI applications.
  • Knowledge of security, authentication, authorization, and enterprise architecture principles.
Preferred Experience
  • Experience building enterprise copilots, knowledge assistants, or conversational AI solutions.
  • Experience with Microsoft Copilot Studio, Power Platform, and enterprise automation technologies.
  • Experience building AI solutions using enterprise data platforms such as Databricks.
  • Experience leveraging enterprise data catalogs, metadata, lineage, and governance capabilities within AI solutions.
  • Experience working with structured and unstructured data at enterprise scale.
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