AI Data Engineer Visa Sponsorship Jobs in Texas
Texas is one of the most active states for AI data engineer visa sponsorship, driven by major tech and energy hubs in Austin, Dallas, and Houston. Companies like Dell, AT&T, ExxonMobil, and a growing field of AI startups regularly hire international candidates for roles spanning data pipelines, machine learning infrastructure, and large-scale analytics systems.
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INTRODUCTION
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
Location
This is onsite role based in Houston, TX
About the job you're considering
Capgemini is seeking an enthusiastic and driven AI/ML Engineer / GenAI Engineer / Data Scientist to join our dynamic Energy & Utilities sector team. This role is designed for emerging talent passionate about leveraging Artificial Intelligence to solve complex industry challenges. The ideal candidate will contribute to innovative projects, applying advanced AI/ML techniques to optimize operations, enhance decision-making, and drive digital transformation for our clients. This is a client-facing role requiring strong technical expertise, communication skills, and a passion for AI-driven innovation.
Your Role
- Collaborate with senior consultants and client teams to identify business challenges and opportunities for AI-driven solutions within the Energy & Utilities sector.
- Assist in the design, development, and deployment of AI/ML models, including Generative AI and Predictive AI solutions.
- Support data collection, cleansing, validation, and preprocessing activities for AI initiatives.
- Work with leading cloud platforms including Azure, AWS, and GCP, leveraging their AI and machine learning services.
- Utilize Databricks, PySpark, and modern AI frameworks to develop scalable analytics and AI solutions.
- Develop agentic AI workflows and intelligent agents to automate business processes and improve operational efficiency.
- Design and implement Retrieval-Augmented Generation (RAG) solutions using modern AI technologies and frameworks.
Your skills and experience
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related quantitative field.
- Minimum of 2 years of professional work experience in Data Science, Artificial Intelligence, or Machine Learning roles.
- Demonstrated experience within the Energy & Utilities sector.
- Strong foundational knowledge of Artificial Intelligence, Machine Learning, and Deep Learning concepts.
- Proficiency in Python or other AI-centric programming languages.
- Experience working with Generative AI concepts including GPT, Claude, Large Language Models (LLMs), and foundation models.
- Knowledge of MLOps practices including model deployment, monitoring, governance, and lifecycle management.
- Experience with LangChain, Retrieval-Augmented Generation (RAG), prompt engineering, and AI orchestration frameworks.
- Hands-on experience developing and consuming REST APIs, JSON-based services, authentication mechanisms, and integration patterns.
- Experience with deployment tools such as Azure DevOps, Docker, AWS ECS, EKS, Fargate, CloudFormation, CodeDeploy, and CI/CD pipelines.
- Strong understanding of data engineering principles and experience working with SQL and NoSQL databases such as MySQL, MongoDB, and Redis.
- Experience utilizing Databricks, PySpark, and cloud-based analytics platforms.
- Strong analytical thinking, problem-solving, and critical reasoning skills.
- Excellent communication, presentation, and interpersonal skills with the ability to effectively engage in client-facing situations.
- Ability to quickly learn emerging technologies and adapt within fast-paced, evolving environments.
- Experience working in Agile/Scrum delivery environments.
- Strong collaboration skills with cross-functional and geographically distributed teams.
Preferred Experience
- Prior experience with OFSE (Oil Field Services & Equipment) or broader Oil & Gas industry operations.
- Experience with data visualization tools and techniques.
- Hands-on experience with Machine Learning frameworks such as TensorFlow, PyTorch, and scikit-learn.
- Experience in Natural Language Processing (NLP) solutions and applications.
COMPENSATION
- The base compensation range for this role in the posted location is $53,580 to $122,400.
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
BENEFITS
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
- Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
- Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
- Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
- Life and disability insurance
- Employee assistance programs
- Other benefits as provided by local policy and eligibility
Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini’s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.
Disclaimers
Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.
This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.
Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.
Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.
AI Data Engineer Job Roles in Texas
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Search AI Data Engineer Jobs in TexasAI Data Engineer Jobs in Texas: Frequently Asked Questions
Which companies in Texas sponsor visas for AI data engineers?
Large employers with established sponsorship programs include Dell Technologies, AT&T, Texas Instruments, ExxonMobil, and Amazon Web Services operations based in Texas. Austin's AI startup ecosystem, including companies in the semiconductor and cloud infrastructure space, also sponsors regularly. Enterprise software firms around the Dallas-Fort Worth metro have a strong track record of filing H-1B visa petitions for data engineering roles.
Which visa types are most common for AI data engineer roles in Texas?
The H-1B is the most common visa category for AI data engineers in Texas, as the role typically qualifies as a specialty occupation requiring a bachelor's degree or higher in computer science, data science, or a related field. Candidates already authorized under OPT or STEM OPT are often hired first, with employers then sponsoring the H-1B. The O-1A is an option for candidates with a demonstrable record of distinction in the field.
Which cities in Texas have the most AI data engineer visa sponsorship jobs?
Austin leads for AI and data engineering sponsorship, anchored by a dense concentration of tech companies and startups. Dallas-Fort Worth is second, driven by telecom, fintech, and enterprise software employers. Houston adds significant volume through energy companies investing in AI-driven data infrastructure. San Antonio has a smaller but growing presence, partly due to cybersecurity and government technology contractors.
How to find ai data engineer visa sponsorship jobs in Texas?
Migrate Mate is built specifically for international job seekers and filters AI data engineer roles in Texas by visa sponsorship availability, saving significant time compared to general job searches. You can browse active listings, filter by city or employer type, and identify companies with a documented history of sponsoring work visas for data engineering positions across Austin, Dallas, Houston, and beyond.
Are there state-specific factors that affect AI data engineer sponsorship in Texas?
Texas has no state income tax, which affects prevailing wage calculations under Department of Labor requirements. Employers must still meet federal prevailing wage levels for the specific metro area, and wage levels differ meaningfully between Austin, Dallas, and Houston. Texas also has strong university pipelines from UT Austin, Texas A&M, and Rice University, which feed talent directly into local employers with existing H-1B sponsorship infrastructure.
What is the prevailing wage for sponsored ai data engineer jobs in Texas?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.