AI Data Engineer Jobs in Austin, TX
AI Data Engineer jobs in Austin, Texas are concentrated in the Domain, Downtown, and the East Austin tech corridor, with strong demand across cloud platforms, fintech, and enterprise software. Employers actively hiring include Apple, Amazon Web Services, and SentiLink. Scan the live roles below and apply to whichever ones fit.
Find AI Data Engineer JobsOverview
Showing 5 of 134+ AI Data Engineer jobs











Imagine what you could do here. At Apple, new ideas have a way of becoming outstanding products, services, and customer experiences very quickly. Bring passion and dedication to your job, and there's no telling what you could accomplish.
Apple's Sales organization generates the revenue needed to fuel our ongoing development of products and services. This, in turn, enriches the lives of hundreds of millions of people around the world. We are, in many ways, the face of Apple to our largest customers.
Apple's US Decision Intelligence (DI) team is looking for a talented individual who is passionate about crafting, implementing, and operating AI solutions that have a direct and measurable impact on Apple Sales and its customers.
Description
We're looking for an AI & Data Security Engineer responsible for securing data across the full AI lifecycle, from data classification and enforcement of access controls to model deployment and agentic applications. This role designs and enforces row-level security policies, API-driven access controls, and role-based data grants across AI pipelines, chat interfaces, and autonomous agents. Partners closely with Data Governance, Legal, and Engineering to align AI data usage with enterprise policy and regulatory requirements. Leads red team exercises to proactively identify vulnerabilities in AI systems and drives remedial actions. Owns the development of security standards and guidelines that enable product teams to build AI applications securely by default, at scale.","responsibilities":"Design and implement security architecture for AI use cases, ensuring secure data access and usage through role-based access controls and authorized provisioning.
Ensure AI use cases are aligned with Apple’s data classification standards, including appropriate data handling, storage, retention requirements and access controls.
Implement and manage user id and persona based row-level security policies for data stored in Snowflake and other data systems connected to US applications.
Implement and maintain row-level security policies based on user identity and persona across DBX and other data platforms supporting U.S. applications.
Design and implement API-based security controls for AI applications, including authentication, authorization and data access policies to protect sensitive information and ensure compliant data consumption.
Lead adversarial testing of AI systems to identify vulnerabilities, drive remediation, and safeguard Apple data from misuse and malicious activity.
Define and enforce data access boundaries for AI agents, governing permitted data sources, actions and restricting sensitive data access.
Define and enforce data access policies for LLM-powered chat applications, governing usage of structured and unstructured data sources, documents and context that may be surfaced in agentic responses.
Partner with Data Governance, Legal, Privacy and Engineering teams to ensure AI data usage complies with enterprise policies, regulatory requirements (e.g., GDPR, CCPA), and internal data governance standards.
Monitor & Audit AI data access pipelines through logging, anomaly detection and audit trails to detect unauthorized access, data exfiltration attempts or policy violations.
Define and enforce US-wide AI data security standards, best practices, and developer guidelines to implement role-based access controls, enabling secure-by-default data practices at scale.
Preferred Qualifications
AI/ML Security Expertise: Direct experience securing AI/ML lifecycles, LLM-powered applications, or autonomous AI agents (e.g., securing RAG architectures, mitigating prompt injection, defining data access boundaries for AI).
Adversarial Testing: Experience leading or participating in red team exercises, penetration testing, or threat modeling specifically tailored to machine learning models and AI systems.
Cross-Functional Leadership: Demonstrated ability to partner effectively with non-technical stakeholders, including Legal, Privacy, and Data Governance teams, to establish and enforce enterprise wide security standards.
Advanced Threat Detection: Experience building or deploying anomaly detection systems to identify malicious activity within complex data pipelines.
Communication Skills: Strong technical writing skills with a track record of creating developer guidelines, security standards, and best practices that enable secure-by-default engineering at scale.
Education & Certifications: Master's degree in a relevant field, or industry recognized security certifications (e.g., CISSP, CISM, Cloud Security certifications).
Minimum Qualifications
8+ years of professional experience in data security, cybersecurity, security architecture, or data engineering with a primary focus on security.
Data Platform Security: Proven hands-on experience designing and implementing Role-Based Access Control (RBAC), row-level, and column-level security policies in modern cloud data platforms (specifically Snowflake and/or Databricks/DBX).
API & Application Security: Strong expertise in API security controls, authentication, and authorization protocols (e.g., OAuth2, OIDC, SAML, JWT) to protect data access.
Programming Skills: Proficiency in Python, Java, Go, or similar languages used for scripting, automation, and building security controls within data pipelines.
Compliance & Privacy: Solid understanding of data privacy regulations (e.g., GDPR, CCPA) and experience translating these regulatory requirements into technical data governance and access controls.
Monitoring & Auditing: Experience implementing security logging, audit trails, and monitoring solutions to detect unauthorized access or data exfiltration.
Education: Bachelor's degree in Computer Science, Cybersecurity, Information Systems, or equivalent practical experience.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
See All 134+ AI Data Engineer Jobs in Austin
Find roles in Austin that match your experience and apply in just a few clicks.
Find AI Data Engineer JobsAI Data Engineer Job Market in Austin
Who's Hiring
- Apple63

- Amazon Web Services8

- SentiLink5

- Amazon4

- Google3

Top Industries Hiring
- Electronics & Hardware61
- Technology & Software32
- Banking & Financial Services10
- Distribution & Wholesale8
- E-Commerce & Online Marketplaces5
AI Data Engineer Jobs in Austin: Frequently Asked Questions
How do I get a ai data engineer job in Austin?
Target Austin's densest hiring pockets first: the Domain's enterprise tech campus cluster, Downtown fintech firms, and East Austin's growing startup scene. Companies here weight hands-on experience with cloud-native pipelines, LLM integration, and tools like Apache Spark or dbt. Candidates who can show shipped ML data infrastructure or real-time pipeline work move faster through Austin hiring loops than those with only academic projects.
Which companies hire ai data engineers in Austin?
Companies currently hiring ai data engineers in Austin include Apple, Amazon Web Services, and SentiLink, per current listings on Migrate Mate as of June 2026. Austin's market skews toward enterprise SaaS, semiconductor, and financial technology employers, many headquartered or with large engineering hubs in the Domain or along the 183 Tech Corridor.
Are there remote ai data engineer jobs in Austin?
Yes, and ai data engineering is relatively remote-friendly given that the work is largely cloud-based and pipeline-driven. About 22% of ai data engineer openings tied to Austin are remote or hybrid as of June 2026, with fully remote roles most common at SaaS and fintech employers. On-site requirements tend to apply to roles involving sensitive data infrastructure or embedded ML teams at semiconductor companies.
How can I get a ai data engineer job in Austin with little or no experience?
The most realistic entry path in Austin is landing a data engineer or analytics engineer role at one of the city's mid-size SaaS or fintech companies, then moving into AI-focused work once you have pipeline experience. Austin employers like IBM, Dell, and early-stage startups in the East Austin corridor regularly hire junior data engineers. Building a portfolio with dbt, Airflow, or a public LLM pipeline project on GitHub gives local hiring managers something concrete to evaluate.
Which industries hire the most ai data engineers in Austin?
The sectors hiring the most ai data engineers in Austin are Electronics & Hardware, Technology & Software, and Banking & Financial Services, based on current listings on Migrate Mate as of June 2026. Austin's position as a semiconductor, enterprise software, and financial technology hub means demand for engineers who can connect large-scale data infrastructure to production AI systems is consistently high across those verticals.
See All 134+ AI Data Engineer Jobs in Austin
Find roles in Austin that match your experience and apply in just a few clicks.
Find AI Data Engineer Jobs