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Ai Rag Jobs in Montgomery, TX (NOW HIRING)

Design privacy guardrails for AI agents, generative AI, RAG pipelines, model inputs and outputs, embeddings, vector stores, and automated data workflows. Reduce Risk While Enabling Innovation:

AI Developer

The Woodlands, TX · On-site

$100K - $120K/yr

Agentic AI: Experience building and orchestrating single‑agent and multi‑agent systems, including prompt engineering, RAG pipelines, and agent decision logic. * Integration Development:

Senior AI Agentic Engineer

Spring, TX · On-site

$93K - $127K/yr

Senior AI Agentic Engineer Location: Spring, TX 77389 (hybrid: 3 days onsite / 2 days remote ... Design and optimize RAG pipelines including document ingestion, chunking strategies, embedding ...

Sr AI Agentic Engineer

Spring, TX · On-site

$93K - $127K/yr

Senior AI Agentic Engineer Spring TX - 3 days in office (Tues/Wed/Thurs) Duration: Full time ... Design and optimize RAG pipelines including document ingestion, chunking strategies, embedding ...

New

Experience with Retrieval-Augmented Generation (RAG), prompt engineering, AI agents. * Familiarity with MLOps, model monitoring, observability, and enterprise AI governance concepts. * Experience ...

Design, develop, and deploy AI-powered applications leveraging large language models (LLMs), retrieval-augmented generation (RAG), intelligent workflows, and related technologies. * Build and ...

Agentic AI Engineer

Conroe, TX · On-site

$100K - $120K/yr

... RAG pipelines, and stateful agent orchestration frameworks (e.g., LangGraph or equivalent). • Experience in deploying and operating LLM/agent workflows in production, including monitoring and ...

Design, develop, and deploy AI-powered applications leveraging large language models (LLMs), retrieval-augmented generation (RAG), intelligent workflows, and related technologies. * Build and ...

Strong proficiency in Python, REST APIs, prompt engineering, RAG pipelines, and stateful agent ... Experience with Azure AI Foundry or comparable platforms for agent development, deployment ...

... RAG pipelines, and stateful agent orchestration frameworks (e.g., LangGraph or equivalent). • Experience in deploying and operating LLM/agent workflows in production, including monitoring and ...

AI Data Scientist Description - About the Position The HP Enterprise AI & Machine Learning ... RAG), and search engines. * Solid technical background. Experience working on software development ...

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Ai Rag information

See Montgomery, TX salary details

$29.1K

$53K

$76K

How much do ai rag jobs pay per year?

As of Aug 9, 2026, the average yearly pay for ai rag in Montgomery, TX is $52,994.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,600.00 and $59,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI researcher?

To thrive as an AI Researcher, you need a strong background in computer science, mathematics, and machine learning, usually with an advanced degree such as a Master's or Ph.D. Proficiency with programming languages like Python, deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with scientific research tools is essential. Critical thinking, creativity, and effective collaboration are vital soft skills for generating novel ideas and working in multidisciplinary teams. These skills and qualities are crucial to drive innovation and solve complex problems in the rapidly evolving field of artificial intelligence.

What is the difference between Ai Rag vs Data Analyst?

AspectAi RagData Analyst
Required CredentialsTypically a diploma or certification in AI, machine learning, or related fieldsBachelor's degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and various industries
Employer & Industry UsagePrimarily in AI development and researchAcross industries for data interpretation and decision-making
Common Search & ComparisonYesYes

Ai Rag and Data Analyst roles share overlapping skills in data handling and analysis, but Ai Rag focuses more on AI-specific applications and machine learning, while Data Analysts concentrate on interpreting data to inform business decisions. Both roles are vital in data-driven industries, with Ai Rag often working in AI development environments and Data Analysts supporting strategic insights across sectors.

What is an AI RAG?

AI RAGs, or Retrieval-Augmented Generation systems, are a type of artificial intelligence that combines the power of retrieving information from large databases or documents with generating human-like text responses. This approach allows AI models to provide more accurate, up-to-date, and contextually relevant answers by referencing external data sources during the generation process. RAGs are commonly used in applications like chatbots, search engines, and customer support systems, where comprehensive and factual responses are important.

What are common challenges faced by AI RAG engineers when integrating retrieval systems with large language models?

AI RAG engineers often encounter challenges such as ensuring seamless integration between retrieval systems and language models, maintaining low latency for real-time responses, and handling the quality and relevance of retrieved data. Additionally, tuning the system to balance retrieval accuracy with generative fluency can be complex, especially when dealing with large or unstructured datasets. Collaboration with data engineers, ML researchers, and product teams is essential to address these challenges and optimize system performance.
What job categories do people searching Ai Rag jobs in Montgomery, TX look for? The top searched job categories for Ai Rag jobs in Montgomery, TX are:
What cities near Montgomery, TX are hiring for Ai Rag jobs? Cities near Montgomery, TX with the most Ai Rag job openings:

Principal Data Privacy Architect

HP Development Company, L.P.

Spring, TX • On-site

Full-time

Medical, Dental, Vision, Life, PTO

Re-posted 10 hours ago


Job description

Principal Data Privacy Architect
Description -
Job Summary
- Role Purpose
• Lead and oversee complex, cross-functional privacy and data protection programs from strategy through implementation, ensuring alignment across business, technical, legal, and compliance stakeholders.
• This role will design and implement scalable, AI-ready data privacy architecture across enterprise data environments, applications, and AI-enabled workflows.
• The Principal Data Privacy Architect will serve as a hands-on subject matter expert responsible for embedding privacy-by-design, consent enforcement, data sovereignty, data loss prevention, and compliance controls into large, complex global data environments.
• The architect will partner closely with Data Engineering, Cybersecurity, Legal, Privacy, AI Governance, Product, and Enterprise Architecture teams to ensure customer, employee, partner, and sensitive enterprise data is accessed, processed, shared, retained, and protected in a compliant, secure, and trustworthy manner.
- Why This Role Matters
• Architect for Trust & Scale: Build reusable privacy architecture patterns that enable secure, compliant, and scalable data usage across platforms, products, and regions.
• Enable Responsible AI: Design privacy guardrails for AI agents, generative AI, RAG pipelines, model inputs and outputs, embeddings, vector stores, and automated data workflows.
• Reduce Risk While Enabling Innovation: Translate privacy, consent, regulatory, and data sovereignty obligations into practical engineering controls that accelerate business outcomes.
Responsibilities
- Think Customer First
• Embed customer trust, transparency, and privacy-by-design principles into enterprise data platforms and customer-facing applications.
• Design consent-aware data access and usage patterns across analytics, personalization, marketing, product telemetry, support, and AI use cases.
• Ensure customer data is collected, processed, shared, retained, and deleted according to approved purposes, consent preferences, and regulatory obligations.
- Innovate for Growth
• Architect reusable privacy engineering components, including APIs, SDKs, reference architectures, automation patterns, and policy-as-code controls.
• Design privacy controls for AI agents and AI-enabled workflows that access, process, summarize, or publish sensitive data.
• Build technical patterns for data minimization, anonymization, pseudonymization, tokenization, encryption, masking, and secure data sharing.
- Act with Integrity
• Partner with Legal, Privacy, Cybersecurity, and Compliance teams to translate global privacy regulations and internal policies into enforceable technical controls.
• Support compliance with GDPR, CCPA/CPRA, LGPD, PIPL, India DPDP Act, data sovereignty mandates, cross-border transfer requirements, and regional data residency obligations.
• Define auditable controls for consent enforcement, access monitoring, retention, deletion, lineage, and compliance evidence collection.
- Build for the Future
• Lead and oversee complex, cross-functional privacy and data protection programs from strategy through implementation, ensuring alignment across business, technical, legal, and compliance stakeholders.
• Establish privacy architecture patterns across data warehouses, lakehouses, metadata platforms, customer data platforms, AI/ML environments, vector databases, and cloud platforms.
• Integrate sensitive data discovery, classification, lineage, DLP, DSPM, IAM, KMS, and monitoring capabilities into the enterprise data ecosystem.
• Advance automated compliance monitoring, privacy control validation, and risk detection across the data lifecycle.
- Work as One Team
• Serve as the program lead for enterprise privacy initiatives, coordinating execution across Data Engineering, Product, Cybersecurity, AI Governance, Legal, Privacy, and Enterprise Architecture organizations.
• Facilitate executive steering committees, project governance reviews, and decision-making forums to ensure successful delivery of strategic privacy programs.
• Track and communicate program milestones, risks, outcomes, and business value to senior leadership and executive stakeholders.
• Collaborate with Data Engineering, Product, AI Governance, Cybersecurity, Legal, Privacy, and Enterprise Architecture teams to embed privacy controls into delivery workflows.
• Provide hands-on architecture guidance for high-risk data initiatives, AI programs, customer data products, and platform modernization efforts.
• Mentor engineers, architects, data scientists, and product teams on privacy engineering best practices.
Strategic & Technical Focus Areas
• AI-Ready Privacy Architecture: Privacy controls for AI agents, generative AI, RAG pipelines, model inputs and outputs, embeddings, vector stores, and automated data workflows.
• Consent & Purpose-Based Usage: Consent propagation, purpose limitation, consent revocation, customer preference enforcement, and downstream data usage controls.
• Data Loss Prevention & Sensitive Data Protection: DLP integration, sensitive data classification, risky sharing detection, exfiltration prevention, and AI prompt/output inspection.
• Data Sovereignty & Compliance Engineering: Regional data residency, cross-border transfer controls, localization requirements, encryption key residency, and audit evidence automation.
• Reusable Privacy Frameworks: Standardized architecture patterns for encryption, masking, tokenization, anonymization, retention, deletion, access control, and monitoring.
Education & Experience & Skills
- Education & Experience
• Bachelor's or master's degree in Computer Science, Engineering, Information Systems, Cybersecurity, Data Engineering, or related field.
• 10+ years of progressive experience in data privacy, data protection, cybersecurity, data architecture, or enterprise data platforms.
• Proven experience architecting privacy and data protection solutions in large, complex, global environments.
• Hands-on experience implementing privacy-by-design, consent management, data sovereignty, DLP, and sensitive data protection controls.
- Technical Expertise
• Strong understanding of global privacy regulations and frameworks, including GDPR, CCPA/CPRA, LGPD, PIPL, India DPDP Act, NIST, ISO 27001, and related privacy/security standards.
• Experience with cloud platforms such as AWS, Azure, or GCP, and enterprise data platforms including data warehouses, lakehouses, data catalogs, metadata platforms, and big data environments.
• Working knowledge of privacy and data protection technologies such as BigID, OneTrust, Securiti, Collibra, Informatica, Microsoft Purview, AWS Macie, Google Cloud DLP, Azure Information Protection, DLP, DSPM, CASB, IAM, and KMS capabilities.
• Strong technical skills in Python, Java, SQL, APIs, Spark, data pipelines, infrastructure-as-code, and policy-as-code.
• Experience with AI/ML, generative AI, AI agents, RAG architectures, vector databases, feature stores, model governance, or AI-enabled data products.
- Leadership & Business Skills
• Ability to translate legal, privacy, compliance, and business requirements into scalable technical architecture.
• Strong communication and influencing skills with engineers, architects, legal teams, privacy teams, product leaders, and senior executives.
• Demonstrated ability to balance customer trust, regulatory compliance, engineering practicality, and business agility.
- Preferred Qualifications
• Certifications such as PMP, CIPP/E, CIPP/US, CIPM, CIPT, CISSP, CCSP, CDPSE, or equivalent.
• Experience building consent management platforms, privacy preference centers, data subject rights automation, or customer data governance capabilities.
• Experience implementing purpose-based access control, attribute-based access control, zero-trust data architecture, or data-centric security models.
• Active industry participation, publications, or memberships related to privacy engineering, AI governance, cybersecurity, or customer trust.
• Experience managing global, cross-functional initiatives with executive-level visibility and measurable business outcomes.
- Cross-Org Skills
• Effective Communication
• Results Orientation
• Learning Agility
• Digital Fluency
• Customer Centricity
Salary
The pay range for this role is 154,400.00 - 227,750.00 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience.
Benefits:
HP offers a comprehensive benefits package for this position, including:
* Health insurance
* Dental insurance
* Vision insurance
* Long term/short term disability insurance
* Employee assistance program
* Flexible spending account
* Life insurance
* Generous time off policies, including;
* 4-12 weeks fully paid parental leave based on tenure
* 11 paid holidays
* Additional flexible paid vacation and sick leave (US benefits overview
[https://hpbenefits.ce.alight.com/])
The compensation and benefits information is accurate as of the date of this
posting. The Company reserves the right to modify this information at any time,
with or without notice, subject to applicable law.
Job -
Data & Information Technology
Schedule -
Full time
Shift -
No shift premium (United States of America)
Travel -
Relocation -
Equal Opportunity Employer (EEO) -
HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).
Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence.
For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: "Know Your Rights: Workplace Discrimination is Illegal"