Senior Principal Engineer - Red Hat Sales Data Management (Raleigh Office)
Red Hat
What will you do?
Enhance existing sales and renewals statistical models with AI-assisted contextual reasoning—without replacing proven methodologies
Augment static sales business rules with configurable, explainable decision layers grounded in authoritative data
Support customer- and territory-specific pattern recognition while maintaining statistical rigor
Leverage Amazon Bedrock–powered LLMs or similar as an augmentation layer, not a system of record
Apply RAG architectures to contextualize sales signals using trusted enterprise knowledge
Automate repeated sales and renewals patterns using Salesforce-connected workflows
Deliver field-facing transparency that explains how traditional signals and augmented insights work together
Maintain audit-ready, compliant sales data and AI workflows aligned with incentive and finance governance
Core ResponsibilitiesTechnical Leadership & ArchitectureOwn and evolve the end-to-end architecture for global sales systems, decision engines, and AI-augmented services
Define standards for sales data modeling, service design, API contracts, event schemas, and hybrid AI integration
Lead architectural reviews and make principled trade-offs across scalability, cost, governance, and explainability
Act as a senior technical advisor across engineering, Sales Ops, Finance, Incentives, and Product
Sales Data, Snowflake & GovernanceDesign and govern enterprise-grade sales and renewals data foundations (Snowflake or similar databases)
Establish data quality, validation, reconciliation, lineage, and observability frameworks
Implement accounting-grade submission calendars and lock processes (daily, monthly, quarterly)
Ensure all sales decisions and AI-augmented outputs are traceable to authoritative sources
Decision Systems, RAG & AI AugmentationArchitect hybrid sales decision systems combining statistical models, deterministic rules, and AI-assisted reasoning
Design and implement Retrieval-Augmented Generation (RAG) to enrich—not override—traditional model outputs
Leverage Openshift AI or Amazon Bedrock or similar to integrate foundation models in a secure, governed, non-authoritative role
Use LLMs for contextual explanation, scenario analysis, and signal enrichment, not primary scoring
Enforce guardrails such as source attribution, confidence thresholds, rule overrides, and human-in-the-loop controls
Salesforce Integration & Intelligent AutomationArchitect systems that ingest and reason over Salesforce data to enhance renewals and pipeline models
Automate sales validation, reconciliation, anomaly detection, and forecasting workflows
Enable proactive identification of upsell, downsell, partial renewal, and other gaming risks
Backend Services, APIs & Field-Facing EnablementArchitect backend services and APIs exposing trusted sales metrics alongside AI-augmented insights
Enable UI experiences that provide clear explanations of decisions and recommendations to the field
Ensure systems meet high standards for reliability, security, performance, and versioning
Cloud, CI/CD & AI OperationsSet patterns for cloud-native architectures across sales data, backend services, and AI augmentation layers
Establish CI/CD standards for sales pipelines, rule engines, and RAG workflows
Define prompt versioning, evaluation, drift detection, and rollback practices
Ensure AI augmentation is observable, controlled, and measurable
Cross-Functional Influence & MentorshipPartner with Sales, Finance, Incentives, Product, and Operations leaders to align systems with business outcomes
Mentor senior engineers on architecture, sales data rigor, and responsible AI usage
Identify systemic risks and lead long-term remediation across global sales platforms
What Sets This Role ApartYou modernize global sales data systems quality and standards without disrupting proven planning and business models
You apply AI where it adds clarity, speed, and context, not authority
You balance innovation with sales trust, governance, and auditability
You influence global GTM outcomes through disciplined, state-of-the-art architectures
What will you bring?
Experience: 10+ years of experience as a Data Engineer, BI Engineer, or Systems Analyst in an enterprise environment with large, complex data sources.
Education: Master’s degree in Computer Science, IT, Engineering, or equivalent experience.
Expert SQL: Deep expertise in relational databases (PostgreSQL, MSSQL, etc.) and query optimization.
Expert Python: Strong programming skills for data querying, cleaning, and presentation, with hands-on experience in data-centric libraries.
Modern Stack Experience: Working knowledge of DBT (Data Build Tool) and Snowflake data warehousing is highly desirable.
ELT/ETL Tools: Experience with Fivetran or similar integration tools.
Autonomy: Ability to manage multiple projects simultaneously in a fast-paced, distributed team environment across different time zones and cultures.
Troubleshooting: Exceptional logic and reasoning skills to troubleshoot complex data issues.
Planning: Ability to think strategically about data architecture and project planning.
#Li-NG1
Pay Transparency
Red Hat determines compensation based on several factors including but not limited to job location, experience, applicable skills and training, external market value, and internal pay equity. Annual salary is one component of Red Hat’s compensation package. This position may also be eligible for bonus, commission, and/or equity. For positions with Remote-US locations, the actual salary range for the position may differ based on location but will be commensurate with job duties and relevant work experience.
About Red Hat
Red Hat is the world’s leading provider of enterprise open source software solutions, using a community-powered approach to deliver high-performing Linux, cloud, container, and Kubernetes technologies. Spread across 40+ countries, our associates work flexibly across work environments, from in-office, to office-flex, to fully remote, depending on the requirements of their role. Red Hatters are encouraged to bring their best ideas, no matter their title or tenure. We're a leader in open source because of our open and inclusive environment. We hire creative, passionate people ready to contribute their ideas, help solve complex problems, and make an impact.
Benefits
● Comprehensive medical, dental, and vision coverage
● Flexible Spending Account - healthcare and dependent care
● Health Savings Account - high deductible medical plan
● Retirement 401(k) with employer match
● Paid time off and holidays
● Paid parental leave plans for all new parents
● Leave benefits including disability, paid family medical leave, and paid military leave
● Additional benefits including employee stock purchase plan, family planning reimbursement, tuition reimbursement, transportation expense account, employee assistance program, and more!
Note: These benefits are only applicable to full time, permanent associates at Red Hat located in the United States.
Inclusion at Red Hat
Red Hat’s culture is built on the open source principles of transparency, collaboration, and inclusion, where the best ideas can come from anywhere and anyone. When this is realized, it empowers people from different backgrounds, perspectives, and experiences to come together to share ideas, challenge the status quo, and drive innovation. Our aspiration is that everyone experiences this culture with equal opportunity and access, and that all voices are not only heard but also celebrated. We hope you will join our celebration, and we welcome and encourage applicants from all the beautiful dimensions that compose our global village.
Equal Opportunity Policy (EEO)
Red Hat is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law.