Top 10 Companies Hiring AI Engineers in Tulsa, OK in 2026

Table of Contents

• Tulsa's AI Kitchen in 2026
• Mazzio's Corporation
• Zeeco
• Matrix Service Company
• Saint Francis Health System
• ConsumerAffairs
• QuikTrip
• ONEOK
• Helmerich & Payne
• BOK Financial
• The Williams Companies
• Your AI Career in Tulsa
• Frequently Asked Questions

Mazzio's Corporation

At first glance, a beloved regional pizza chain seems an unlikely AI destination. Yet Mazzio's offers a compelling arena where data science has a direct, tangible impact on high-volume delivery and franchise operations. Their corporate team in Tulsa uses machine learning to modernize every facet of the business, turning data into a key ingredient for efficiency and customer satisfaction.

Projects focus on pragmatic predictive analytics, such as demand forecasting for optimal staffing and dough production to minimize waste. Engineers also build recommendation engines for digital ordering platforms to personalize the customer experience. The tech stack is purpose-built, centered on Python, SQL, and cloud data warehouses to handle operational data flows.

With a small, high-impact data team, an engineer's work directly influences the operational strategy of an iconic brand. Mid-level AI roles here command a solid $90k-$130k, aligning with the broader Tulsa market where, according to Robert Half salary data, AI/ML professionals can earn competitive salaries. The interview process typically involves one-on-one discussions and practical skills tests relevant to business analytics, as outlined in the company's hiring approach.

This role exemplifies how Tulsa’s diverse economy offers unique AI applications far beyond the expected tech sectors, proving that impactful machine learning can thrive anywhere there's data, a complex operation, and a problem to solve.

Zeeco

Headquartered in the Tulsa area, Zeeco is a global leader where AI meets an urgent, physical-world mission: combating climate change at the industrial source. The company's research and development teams, staffed with PhDs and senior ML engineers, leverage machine learning to model and optimize the complex physics of combustion for environmental sustainability.

Projects are deeply technical and focused on tangible outcomes, including building sophisticated Digital Twin models for industrial burners and boilers, and developing real-time machine learning systems for emissions monitoring and reduction. The tech stack reflects this specialization, combining Python and MATLAB with advanced Computational Fluid Dynamics (CFD) software. This is deep-tech R&D where an algorithm can directly lower the carbon footprint of heavy industry.

"We focus on leveraging advanced technologies to design and develop robust data solutions that drive tangible value." - PwC Industry Leader on tech-driven environmental solutions.

Salaries command a premium for this advanced, mission-driven work, ranging from $110k-$150k for mid-level engineers up to $155k-$190k for senior roles, positioning Zeeco at the higher end of Tulsa's specialized industrial tech salary bands. For engineers passionate about applying AI to one of society's most critical challenges, Zeeco offers a unique and impactful path within Tulsa's robust industrial landscape.

Matrix Service Company

Digitizing the "heavy" industries of construction and energy infrastructure is the fresh frontier where Matrix Service Company operates. As a leading provider of construction and maintenance services, Matrix integrates artificial intelligence to bring unprecedented intelligence to physical project sites and planning offices, transforming age-old practices with modern data science.

The primary applications are profoundly practical: employing computer vision for real-time construction site safety monitoring to prevent accidents, and developing machine learning models for more accurate project cost estimation and scheduling. Engineers here work on turning terabytes of site data into actionable insights that keep workers safe and projects on budget.

AI engineers are integrated into Project Controls and Technology Innovation groups, collaborating directly with veteran project managers. The tech stack is built for integration, leveraging Python and Azure alongside specialized Building Information Modeling (BIM) software. This role is for builders who want to see their code manifest in safer, more efficient physical projects.

Salaries are competitive within Tulsa’s industrial tech sector, with mid-level roles earning $95k-$130k and senior positions reaching $135k-$170k. The interview process is known for its conversational approach, focusing on past project experience and problem-solving, as detailed in industry hiring insights. For those seeking a career at the intersection of data and durable infrastructure, Matrix represents a pivotal player in Tulsa's growing applied AI landscape.

Saint Francis Health System

For AI engineers driven by purpose, Saint Francis Health System offers a powerful mission: deploying machine learning to directly improve patient outcomes. As the region's largest healthcare provider, its work sits at the critical intersection of clinical informatics and IT, applying predictive analytics to both operational excellence and direct patient care.

Projects range from predicting patient readmission risks and optimizing hospital resource management to developing cutting-edge, AI-assisted radiology imaging. Engineers must be proficient not only in Python and SQL but also in navigating the complex, privacy-sensitive landscape of healthcare data within systems like Epic, all under the strict governance of HIPAA regulations.

"We're focused on the intentional adoption of evidence-based clinical AI." - Amol Nirgudkar, Healthcare Leadership Professional, on the strategic approach to healthcare AI.

This high-impact responsibility commands competitive salaries, with mid-level roles at $105k-$140k and senior positions reaching $145k-$180k. The collaborative environment, where data scientists work directly with clinicians, ensures technology serves patient needs first. As highlighted in the broader national talent demand for AI in healthcare fields, this role represents a career where technical rigor meets profound human impact, strengthened by Tulsa's central location and growing med-tech ecosystem.

ConsumerAffairs

Tulsa's ConsumerAffairs has matured from a startup into a well-funded, product-led scale-up where natural language is the core commodity. As a leading customer-insight platform processing massive volumes of user reviews and brand data, it provides a rich environment for AI engineers fascinated by language models and sophisticated recommendation systems.

The work is central to the product itself. Engineers develop NLP models for automated review summarization and sentiment analysis, build sophisticated recommendation engines to match consumers with brands, and create lead-scoring algorithms. This involves working with massive text datasets that serve as an ideal playground for LLM fine-tuning and advanced sentiment analysis, offering hands-on experience with the technologies shaping modern AI.

Engineers operate in agile, product-focused teams, owning features from research to production. They utilize a modern stack including Python, TensorFlow, Hugging Face, and PostgreSQL. The culture mirrors a standard tech scale-up, with an interview process that typically involves a recruiter screen, a technical challenge, and team fit interviews.

According to local salary data from Robert Half, AI/ML professionals at this level in Tulsa can expect to earn $110k-$160k. For engineers seeking the energy of a product-driven tech company with the stability of an established player, all within Tulsa's growing machine learning job market, ConsumerAffairs stands out as a unique opportunity to shape how businesses understand their customers.

QuikTrip

QuikTrip's reputation is for convenience, but behind the scenes, its Tulsa-based IT division runs a sophisticated data operation managing one of the highest retail transaction volumes in the country. For an AI engineer, QT represents the ultimate challenge in applied machine learning: optimizing high-frequency, high-volume data where even a fractional improvement translates into massive operational and financial gains.

The projects are critical to core business functions. Teams work on dynamic pricing models, AI-driven inventory and supply chain optimization, and pioneering experiments with computer vision for checkout-free stores. Engineers typically join large, specialized internal teams like "Data Insights" or "Retail Tech" squads, utilizing a stack that includes Java, Python, Azure, and SQL Server to handle this relentless data flow.

The interview process is known for its thoroughness, combining technical panels with comprehensive personality and aptitude assessments designed to find candidates who thrive in QT's fast-paced, efficiency-driven culture. This demand for top talent is part of a broader trend, as noted in analysis of the unexpected winners in AI hiring across industries.

Salaries are strong within the Tulsa market, with mid-level roles paying $100k-$140k and senior engineers earning $150k-$185k. While these local roles may pay $30k-$50k less than coastal remote positions, as discussed in Tulsa tech community forums, the lower cost of living and the chance to solve complex, large-scale retail problems present a compelling value proposition for engineers looking to make a tangible impact.

ONEOK

As a major midstream service provider, ONEOK applies artificial intelligence to the complex, physical flow of natural gas liquids, creating a fascinating nexus of thermodynamics and digital intelligence. The company's initiatives focus on driving monumental efficiencies across its vast network of processing plants and logistics, where machine learning models manage the movement of physical energy products across the country.

Key projects are critical to operational integrity and market responsiveness. Teams build sophisticated demand forecasting models for natural gas products, implement anomaly detection systems to ensure smooth plant operations, and optimize logistics and supply chain movements. This work is supported by a hybrid team structure, where IT-led AI architecture groups provide robust frameworks for business-unit data scientists, ensuring solutions are both technically sound and operationally relevant.

The tech stack is enterprise-focused, leveraging Python, Microsoft Azure, and Scikit-learn for development and deployment. The interview process mirrors this practical, business-integrated approach, typically involving behavioral-based interviews via Microsoft Teams and technical assessments focused on real-world data engineering skills. This reflects a growing trend in the sector, as seen in Tulsa's demand for applied AI talent.

Salaries for these crucial roles underscore the value placed on this work, ranging from $115k-$150k for mid-level engineers to $160k-$195k for senior contributors. For AI professionals, a role at ONEOK means building models that don't just predict data points but actively manage the physical and economic currents of North America's energy landscape, all from a strategic hub in Tulsa.

Helmerich & Payne

Helmerich & Payne has undergone a radical transformation, evolving from a traditional drilling contractor into a technology-led automation company through its H&P Technologies division. This is where artificial intelligence meets heavy machinery in some of the most remote and demanding environments on earth, defining the cutting edge of "Edge AI" applications.

The work focuses on autonomy and real-time intelligence: developing self-operating drilling systems, implementing computer vision for enhanced rig site safety monitoring, and creating predictive models of subsurface geology. The team is intensely engineering-focused, with ML engineers collaborating directly with robotics and mechanical specialists, often processing noisy, real-world sensor data streamed directly from active rigs.

The specialized tech stack reflects this unique challenge, involving C++, Python, TensorFlow, and the Robot Operating System (ROS). This deep specialization commands top-tier salaries in the Tulsa market, with mid-level roles earning $130k-$170k and Staff or Principal engineers reaching $175k-$225k. These figures are supported by broader data on Tulsa's high-end machine learning salaries.

The interview process involves technical deep dives into systems design and the ability to work with imperfect, real-world data, as detailed in H&P's hiring approach for senior engineering roles. For an AI engineer passionate about building intelligent systems that operate autonomously in the physical world, H&P offers one of the most distinctive and technically challenging career paths not just in Tulsa, but in the global energy technology sector.

BOK Financial

In the highly regulated world of finance, BOK Financial has cultivated a mature and rigorous machine learning practice that serves as a premier Tulsa destination for AI engineers who appreciate structure, robust governance, and complex problem-solving within defined boundaries. The work is critical to the bank's core stability and customer service, focusing on applications where accuracy and explainability are paramount.

Projects directly safeguard assets and streamline operations, including developing advanced fraud detection systems, building automated credit scoring models, and employing natural language processing for customer service sentiment analysis and regulatory compliance. The specialized "Enterprise Data Science" team operates with a high degree of methodological rigor, requiring models to be not only predictive but fully interpretable to meet strict auditing standards.

The tech stack strategically blends modern tools like Python, AWS SageMaker, and Snowflake with established legacy systems such as SAS, reflecting the balance between innovation and reliability required in banking. This deep, regulated environment is mirrored in a multi-stage interview process that includes technical screenings and deep dives into statistical modeling theory, as outlined on the BOK Financial careers portal.

Salaries are competitive within Tulsa's financial tech sector, with mid-level data scientists earning $110k-$145k and senior roles paying $155k-$190k. As the company seeks leaders who are "product-minded with strong business acumen," it represents a career path where AI expertise directly shapes financial strategy and risk management, contributing to the strength of one of the nation's top regional banks from its Tulsa headquarters.

The Williams Companies

Topping this list is The Williams Companies, a Fortune 500 energy infrastructure giant, distinguished by the sheer physical scale and tangible national impact of its AI ambitions. Here, machine learning functions as the nervous system for one of the nation's largest natural gas networks, where models don't just analyze data - they actively manage critical infrastructure that powers homes and industries across the continent.

AI engineers at Williams tackle problems of immense scope, building predictive maintenance models for pipelines spanning thousands of miles, optimizing real-time gas flow across a continent, and deploying sophisticated satellite-based leak detection systems. The tech stack - including Python, Azure ML, PyTorch, and Databricks - is tasked with processing terabytes of sensor data from a vast IoT network, representing some of the most challenging data engineering and time-series forecasting work in the industry.

Engineers operate within a centralized "Digital Transformation" hub while embedding directly with operations teams, ensuring their work has immediate, real-world effect on national energy reliability and safety. This critical role commands Tulsa’s top AI salaries: $125k-$165k for mid-level positions and $170k-$210k+ for senior or principal engineers.

While these local roles may pay $30k-$50k less than comparable coastal positions, as noted in local tech community discussions, the trade-off is compelling. The lower cost of living in Tulsa, combined with the unmatched magnitude of the problems solved - literally keeping the lights on and homes warm - offers a unique value proposition. For an AI engineer seeking to deploy models at a truly infrastructural scale, Williams represents the peak of applied machine learning, proving that groundbreaking work thrives in Tulsa, supported by initiatives like the city's talent boom and competitive Oklahoma AI salary standards.

Your AI Career in Tulsa

Tulsa’s AI landscape is a testament to applied intelligence, where machine learning solves fundamental problems in energy, finance, healthcare, and logistics. The career path here is defined not by Silicon Valley prestige, but by the substantive weight of the challenges you’ll tackle - from continental energy networks to autonomous industrial systems - all supported by a lower cost of living and a community invested in growth.

Building the skills to enter this market is more accessible than ever. For aspiring AI professionals in Tulsa, bootcamps like Nucamp's 25-week Solo AI Tech Entrepreneur program offer a focused, affordable pathway. With tuition at $3,980 and a curriculum in LLM integration and AI product development, it aligns perfectly with Tulsa’s growing startup and innovation ecosystem. Similarly, their 15-week AI Essentials for Work program provides practical skills for professionals aiming to leverage AI in established industries.

These programs, with their flexible schedules and community-based learning model in over 200 US cities including Tulsa, demonstrate that a high-impact AI career doesn't require a coast-to-coast move or a six-figure education. With a reported 78% employment rate for graduates, they provide a viable on-ramp to the roles detailed throughout this list.

Whether you're drawn to the infrastructural scale at Williams, the regulatory rigor at BOK Financial, or the physical-world robotics at H&P, Tulsa offers a compelling proposition: a career where your work has immediate, substantive impact, backed by a supportive network and accessible training opportunities right in your own community.

Frequently Asked Questions