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Ai Rag Jobs in Pasadena, TX (NOW HIRING)

Hp

Principal Data Privacy Architect

Spring, TX

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:

AMSYS Talent

Sr Gen AI Engineer

Houston, TX · On-site

$99K - $137K/yr

Senior Generative AI Engineer (Azure / RAG / LLM) We're looking for a hands-on Senior AI Engineer to build and deploy production-grade generative AI solutions. This role focuses on taking use cases ...

AMSYS Talent

AI Product Delivery Lead

Houston, TX · On-site

Define AI use cases (RAG, automation, agentic workflows) * Translate business needs into clear requirements + user stories * Drive product direction + roadmap for AI solutions * Manage projects ...

INSPYR Solutions

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 ...

Brooksource

AI Engineer

Houston, TX · On-site

$70 - $90/hr

Develop RAG pipelines (ingestion → retrieval → generation) * Work with orchestration frameworks ... Azure AI Foundry * LangGraph (or similar) * Copilot / Microsoft AI stack * Agent registries ...

NATIONMIND LLC

AI Architect Lead

Houston, TX · Remote

$45 - $50/hr

... RAG workflows, tool-calling systems, and enterprise chatbot platforms. · Strong understanding of LLM ecosystems including OpenAI, Claude, ChatGPT Enterprise, Azure OpenAI, Amazon Bedrock, Google ...

myDNA, Inc.

Senior AI Developer

Houston, TX · On-site

$52 - $68.75/hr

Builds retrieval-augmented generation (RAG) pipelines - document ingestion, chunking, embeddings ... Builds and operates AI systems for audit-readiness - data lineage, prompt and model version ...

NATIONMIND LLC

AI Engineer Developer

Houston, TX · Remote

$40 - $45/hr

Key Technical Skills: · Python, TypeScript, Node.js, Java, Go · AI Agents & GenAI Applications · RAG (Retrieval-Augmented Generation) · LLM APIs (OpenAI, Claude, Azure OpenAI, Bedrock, Vertex AI ...

Marencor

Gen AI/ML Solution Architect

Houston, TX · On-site

$60.25 - $79.25/hr

Position: Gen AI/ML Solution Architect Location: Houston, TX - (5 days onsite per week) Notes ... Develop Retrieval-Augmented Generation (RAG) pipelines for intelligent document retrieval and ...

Kirkland & Ellis

Innovation AI Developer

Houston, TX · On-site

... RAG pipelines using vector databases and knowledge graph solutions. Develop AI agents that automate multi-step workflows and enable sophisticated task orchestration. • Create reusable libraries ...

Viridien

Head of Applied AI Products

Houston, TX · On-site

... enhanced RAG (Retrieval-Augmented Generation) systems and AI-assisted research tools. • Lead the development of AI-native applications and tools. • Implement tool-calling and orchestration ...

FIRST SERVICE CREDIT UNION

AI Engineer

Houston, TX · On-site

Role: The AI Engineer holds primary responsibility for architecting and implementing FSCU's on ... Designs and builds LLM-based applications, including RAG pipelines, agentic search, and vector ...

FIRST SERVICE CREDIT UNION

AI Engineer

Houston, TX

Role: The AI Engineer holds primary responsibility for architecting and implementing FSCU's on ... Designs and builds LLM-based applications, including RAG pipelines, agentic search, and vector ...

FIRST SERVICE CREDIT UNION

AI Engineer

Houston, TX · On-site

Role: The AI Engineer holds primary responsibility for architecting and implementing FSCU's on ... Designs and builds LLM-based applications, including RAG pipelines, agentic search, and vector ...

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Showing results 1-20

All JobsAi Rag JobsAi Rag Jobs in Pasadena, TX

Ai Rag information

See Pasadena, TX salary details

$29.2K

$53.2K

$76.3K

How much do ai rag jobs pay per year?

As of Jul 27, 2026, the average yearly pay for ai rag in Pasadena, TX is $53,220.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,800.00 and $59,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI Researcher, and why are they important?

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.

Which AI is best at RAG?

For an AI Rag role, the best AI systems for Retrieval-Augmented Generation (RAG) tasks typically include models like OpenAI's GPT-4, Google's Bard, and Meta's Llama 2, which are capable of integrating retrieval components with language generation. Success in RAG depends on the model's ability to efficiently access and incorporate external data, as well as the implementation of effective retrieval mechanisms and fine-tuning. Skills in natural language processing, knowledge of retrieval systems, and experience with relevant tools are essential for this role.

What engineer makes 500,000 a year?

Senior software engineers, especially those working in high-demand fields like artificial intelligence or machine learning at large tech companies, can earn $500,000 or more annually. Compensation often includes base salary, bonuses, and stock options, and requires advanced skills, extensive experience, and often a master's or Ph.D. in a related field.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer, AI research director, or executive roles like AI CTO. These roles often require advanced skills in data science, deep learning, and experience with tools like TensorFlow or PyTorch, along with a strong track record of innovation and leadership in the field.

What are AI RAGs?

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.

Which 3 jobs will survive AI?

AI Rag is a role that involves managing and interpreting AI outputs, and jobs that require complex problem-solving, creativity, and emotional intelligence are more likely to survive AI automation. Examples include healthcare professionals, skilled tradespeople, and roles in education. These jobs often require human judgment, interpersonal skills, and adaptability that AI cannot fully replicate.

What are some common challenges faced by AI RAG (Retrieval-Augmented Generation) 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 cities near Pasadena, TX are hiring for Ai Rag jobs? Cities near Pasadena, TX with the most Ai Rag job openings:
Ai Rag jobs near you
Principal Data Privacy Architect

Principal Data Privacy Architect

HP Development Company, L.P.

Spring, TX • On-site

Full-time

Medical, Dental, Vision, Life, PTO

Posted 20 days ago

Job description

Principal Data Privacy Architect
Description -
Job Summary
- Role Purpose
  • 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
  • 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
  • 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 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.

- 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"

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