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Ai Integration Engineer Jobs in Texas (NOW HIRING)

Kinetik

OT Integration Engineer

Midland, TX · On-site

$102K - $137K/yr

As an OT Integration Engineer at Kinetik, you design, build, and support the pipelines, APIs, SQL ... AI Analytics Engineers to understand data requirements for forecasting, optimization, predictive ...

Cacheflow

Cloud Integration Engineer

Austin, TX · On-site

$102 - $135.40/hr

We believe in harnessing AI responsibly to unlock new possibilities, and we're looking for ... Cloud Integration Engineer Overview We are seeking a skilled AWS Cloud Integration Engineer to ...

SLB

Artificial Intelligence Engineer

Houston, TX · On-site

$99K - $133K/yr

The Domain AI Integration Engineer will be responsible for integrating advanced Artificial Intelligence and Generative AI capabilities into the company's domain software systems (e.g. Delfi, Lumi ...

McLane Company

MDM Integration Engineer

Temple, TX · On-site

$84K - $113K/yr

Summary McLane is seeking an MDM Integration Engineer to design, develop, and support scalable ... Vertex AI * Experience implementing and managing APIs through APIGEE. * Strong knowledge of ...

Miro

AI Integrations Engineer

Austin, TX · Remote

$103K - $138K/yr

We are looking for an AI Integrations Engineer to be the connective tissue between our core ... Integration & Middleware Expertise: Proven, hands-on experience building complex automations on ...

Ericsson

Integration Engineer (Entry Level)

Plano, TX · On-site

$8.5K - $11K/mo

... AI • Expertise in programming, automation, and OS solutions and design. • Ability to ... Integration Engineer Compensation and Benefits at Ericsson At Ericsson, we know that our people are ...

Ericsson

Integration Engineer (Entry Level)

Plano, TX

$8.5K - $11K/mo

Must demonstrate good understanding/knowledge of AI Expertise in programming, automation, and OS ... Integration Engineer Compensation and Benefits at Ericsson At Ericsson, we know that our people are ...

ISEE

Autonomous Vehicle Integration Engineer

Dallas, TX

$102K - $138K/yr

ISEE is seeking a detail-oriented AV Integration Engineer. Role responsibilities include ... intelligence (AI) tools to support parts of the hiring process, such as reviewing applications ...

ISEE

Autonomous Vehicle Integration Engineer

Dallas, TX · On-site

$102K - $138K/yr

ISEE is seeking a detail-oriented AV Integration Engineer. Role responsibilities include ... intelligence (AI) tools to support parts of the hiring process, such as reviewing applications ...

Allen Control Systems

Test Integration Engineer

Austin, TX · On-site

$103K - $138K/yr

Navy electrical engineers with deep experience in robotics and software, ACS brings together AI ... We are looking for a Test Integration Engineer to join our team, focusing on system integration ...

Allen Control Systems

Test Integration Engineer

Austin, TX · On-site

$103K - $138K/yr

Navy electrical engineers with deep experience in robotics and software, ACS brings together AI ... We are looking for a Test Integration Engineer to join our team, focusing on system integration ...

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Showing results 21-40

All JobsAi Integration Engineer JobsAi Integration Engineer Jobs in Texas

Ai Integration Engineer information

See Texas salary details

$41.5K

$115.8K

$161.6K

How much do ai integration engineer jobs pay per year?

As of Sep 4, 2026, the average yearly pay for ai integration engineer in Texas is $115,781.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,900.00 and $130,400.00 per year, depending on experience, location, and employer.

What is an AI integration engineer?

AI Integration Engineers are professionals who specialize in implementing artificial intelligence solutions into existing systems, products, or workflows. They work closely with data scientists, software developers, and business teams to ensure that AI models and technologies are effectively deployed and seamlessly integrated. Their responsibilities often include customizing AI tools, developing APIs, ensuring data compatibility, and monitoring performance post-integration. These engineers play a crucial role in bridging the gap between AI research and practical business applications.

What are some common challenges faced by AI integration engineers when deploying machine learning models into existing business systems?

AI Integration Engineers often encounter challenges such as ensuring compatibility between machine learning models and legacy systems, managing data privacy and security, and optimizing model performance for real-time applications. They must also address issues related to model scalability and monitoring, as well as facilitate smooth collaboration between data science, IT, and business teams. Overcoming these challenges requires strong problem-solving skills, effective communication, and a deep understanding of both AI technologies and enterprise infrastructure.

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

To thrive as an AI Integration Engineer, you need a solid background in computer science, programming (Python, Java, or similar), and experience with AI/ML frameworks, often supported by a bachelor's degree in a related field. Familiarity with cloud platforms (such as AWS, Azure, or Google Cloud), API development, and tools like TensorFlow or PyTorch is typically required. Strong problem-solving abilities, collaboration, and clear communication are essential soft skills for bridging technical and business needs. These competencies ensure successful deployment and seamless integration of AI solutions into existing systems, driving innovation and business value.

What is the difference between Ai Integration Engineer vs Data Scientist?

AspectAi Integration EngineerData Scientist
Required CredentialsBachelor's in CS, Engineering, or related; certifications in AI/ML toolsBachelor's or higher in CS, Statistics, or related; advanced degrees common
Work EnvironmentDeveloping and deploying AI solutions, integrating AI APIs into applicationsAnalyzing data, building predictive models, interpreting complex datasets
Employer & Industry UsageTech companies, AI service providers, software firmsResearch institutions, tech companies, finance, healthcare

While both roles involve AI, the Ai Integration Engineer focuses on implementing and integrating AI solutions into applications, whereas the Data Scientist analyzes data to develop models and insights. The roles often overlap but differ mainly in their primary focus: deployment versus analysis.

Are AI Integration Engineers highly paid?

AI Integration Engineers typically earn higher-than-average salaries due to their specialized skills in AI systems, programming, and data analysis. Compensation varies based on experience, location, and industry, but they are generally well-compensated compared to many other engineering roles.

What are popular job titles related to Ai Integration Engineer jobs in Texas?

For Ai Integration Engineer jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Ai Integration Engineer jobs in Texas look for?

The top searched job categories for Ai Integration Engineer jobs in Texas are:

What cities in Texas are hiring for Ai Integration Engineer jobs?

Cities in Texas with the most Ai Integration Engineer job openings:

Ai Integration Engineer jobs near you
Infographic showing various Ai Integration Engineer job openings in Texas as of August 2026, with employment types broken down into 66% Full Time, 18% Part Time, and 16% Contract. Highlights an 100% In-person job distribution, with an average salary of $115,781 per year, or $55.7 per hour.

OT Integration Engineer

Kinetik

Midland, TX • On-site

$102K - $137K/yr

Full-time

Posted 15 days ago

Key responsibilities

  • Design, build, and support data pipelines, APIs, SQL models, data products, and integration services for operational and business data.

  • Implement monitoring, logging, alerting, and troubleshooting procedures for production data pipelines and integration services.

  • Coordinate with various teams to ensure data flow accuracy, system dependencies, and support high-priority projects related to OT data integration.

Job description

Kinetik is strategically located in the heart of the Delaware Basin in the Permian, one of the fastest growing areas for oil and gas development in the world. We provide the gathering, compression, processing, transportation and water management services required to bring natural gas, natural gas liquids and crude oil to market and are dedicated to providing the best service and netback for our customers. We are driven to be best-in-class and committed to growing our existing assets in the Permian Basin through both greenfield and acquisition opportunities.
Kinetik employees have decades of experience in West Texas and provide all the important services our customers need to deliver gas and crude oil production to market, which include gathering, transportation, compression, processing and produced water management.
Essential Duties and Responsibilities:
As an OT Integration Engineer at Kinetik, you design, build, and support the pipelines, APIs, SQL models, data products, and integration services that help operational and business data move reliably across the organization. You play a critical role that enables Kinetik to shape its large collection of operational and business data into insights that empower our employees, improve safety, and streamline operations.
Data pipeline and integration engineering
  • Construct and support real-time and batch data pipelines connecting SCADA platforms, historians, databases, APIs, business systems, and enterprise analytics environments.
  • Establish and promote reliable integration patterns for operational data movement across OT, DMZ, cloud, and enterprise environments.
  • Deploy, secure, and maintain industrial MQTT / Sparkplug B broker infrastructure across OT, DMZ, and analytics network zones, including edge brokers near source systems, broker bridging and aggregation into enterprise-level brokers, and store-and-forward resilience.
  • Organize and simplify integrations involving SCADA, historian, FlowCal, SQL Server, Ignition, AVEVA / Wonderware, MQTT / Sparkplug B, OPC UA, REST APIs, Solace, HighByte, and new business systems.

API, SQL, and data product development
  • Develop APIs, services, SQL models, views, stored procedures, and reusable data access patterns that expose relevant OT data to business and analytics consumers.
  • Define and maintain data contracts, schemas, naming standards, interface patterns, and documentation for operational data products.

Reliability, monitoring, and troubleshooting
  • Implement monitoring, logging, alerting, retry behavior, fault handling, and recoverability patterns for production data pipelines and integration services.
  • Investigate data pipeline failures, latency issues, missing data, schema changes, stale data, duplicate records, and unexpected data movement behavior.
  • Distinguish integration issues from source-system issues or downstream model/tool issues and assist primary stewards with corrections.

Software engineering and change control
  • Reduce dependence on manual file handling, duplicated queries, spreadsheet-driven workflows, unmanaged scripts, and fragile point-to-point interfaces.
  • Apply source control, modular design, testing, versioning, peer review, CI/CD, and maintainable development practices where appropriate.
  • Support controlled change management for schemas, APIs, SQL objects, data pipeline logic, and integration interfaces.

Team support and documentation
  • Coordinate with analytics team members to hunt down problems in the OT Data Ecosystem.
  • Maintain documentation for supported systems.

Collaboration and communication expectations
  • Assist OT Systems Specialists to ensure data pipeline assumptions match field, SCADA, historian, FlowCal, and measurement-system realities.
  • Assist AI Analytics Engineers to understand data requirements for forecasting, optimization, predictive maintenance, RAG systems, AI assistants, and decision-support tools.
  • Coordinate with IT / Infrastructure, Operations, Measurement, Commercial, Environmental, Engineering, and other stakeholders during integration design, troubleshooting, and support.
  • Support other OT Analytics team members during workload spikes, incidents, commissioning efforts, dashboard/tool development, or high-priority projects, while preserving the primary ownership boundaries defined for each role.
  • Communicate data flow, system dependencies, latency, availability, failure modes, and technical tradeoffs clearly to technical and non-technical audiences.
  • Preserve clear ownership of data pipelines, APIs, SQL models, schemas, and data products while supporting the broader OT data value chain.
  • All other duties as assigned.

Education and/or Work Experience Requirements:
Required:
  • Bachelor's degree in computer science, engineering, information systems, or a related technical field;
    equivalent industry experience will be considered.
  • 5+ years of relevant experience in data, integration, software engineering, industrial automation, OT/IT analytics, or related technical work.
  • Strong SQL and relational database skills, including data validation, troubleshooting, reusable data access patterns, views, stored procedures, and timestamp-based analysis.
  • Experience designing, supporting, and troubleshooting production data pipelines, APIs, SQL models, integration services, scripts, or automated workflows.
  • Working knowledge of structured data formats, APIs, data movement patterns, data contracts, schema discipline, and secure system-to-system integration.
  • Experience supporting production systems, monitoring, logging, alerting, fault handling, recovery, and troubleshooting.
  • Experience with MQTT / Sparkplug B, OPC UA, REST APIs, historian integrations, SQL Server integrations, event streaming, or similar technologies.

Preferred:
  • Experience with, and preferably experience deploying and administering, MQTT brokers (such as Solace, HiveMQ, EMQX, or Chariot), including broker bridging or aggregation across network zones, topic namespace design, and Sparkplug B concepts such as birth/death certificates and metric metadata.
  • Experience with HighByte or similar industrial data integration platforms.
  • Experience with Python, PowerShell, containerization, Windows and Linux environments, source control, testing, peer review, CI/CD, or related maintainable development practices.
  • Experience in oil and gas, midstream, utilities, manufacturing, or another industrial environment.
  • Experience with AVEVA Wonderware, AppServer, AVEVA Historian, Ignition (including MQTT Engine / MQTT Transmission modules), FlowCal, Autosol ACM, TopServer / Kepware, or related OT and measurement systems.
  • Familiarity with Databricks, Palantir Foundry, Power BI, Snowflake, or similar analytics and data platforms.
  • Understanding of OT cybersecurity basics, industrial protocols, and segmented network environments.
  • Experience replacing point-to-point interfaces or replicated-historian architectures with publish/subscribe data movement, including preserving tag metadata and data quality context through the pipeline.

Working Conditions:
  • Will be working in an office environment with prolonged periods of sitting and working on a computer.
  • Will work outdoors in adverse or extreme weather conditions on occasion
  • Will be required to frequently drive to other field facilities within their assigned region.
  • Primarily office-based, with most work performed using computers, databases, development tools, analytics platforms, and remote system access
  • Regular collaboration with Executive, Operations, Measurement, Commercial, Engineering, IT, and OT department members to understand business needs and validate analytics solutions
  • Limited field travel required, typically a few site visits per year, with occasional additional travel to operational sites, compressor stations, or field locations
  • May occasionally support urgent analytics, reporting, model, or data-related issues that affect operational or commercial decision-making

Physical Requirements:
  • Ability to safely and successfully perform the essential job functions consistent with the ADA, FMLA and other federal, state and local standards, including meeting qualitative and/or quantitative productivity standards.
  • Ability to maintain regular, punctual attendance consistent with the ADA, FMLA and other federal, state and local standards
  • Ability to work effectively in all working conditions noted above.
  • Must be able to communicate clearly and professionally in person, over the telephone, and in virtual communication settings with technical and non-technical personnel.
  • Ability to sit for extended periods while working at a computer and performing remote system configuration.
  • Ability to occasionally travel to field locations, compressor stations, and other operational sites and safely navigate industrial environments.
  • Must be able and willing to work extended hours and respond to urgent operational issues as business needs require.
  • Ability to lift standard computer equipment, laptops, monitors, and related materials as needed.

Kinetik is an equal employment opportunity employer and does not discriminate against qualified applicants on the basis of actual or perceived race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, pregnancy, veteran status, genetic information, citizenship status, or any other basis prohibited by law.

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