Applied AI Engineer Jobs in Texas
Applied AI Engineer jobs in Texas are among the most active in the country, concentrated in enterprise software, defense technology, energy, and financial services, with openings at every level from entry-level ML engineer to senior principal. Austin, Dallas, and Houston anchor most of the hiring, with employers like Dell Technologies, AT&T, and ExxonMobil maintaining deep and lasting AI engineering practices in the state. The most in-demand specialties are large language model deployment, computer vision systems, and MLOps infrastructure. Find a role that fits below and apply directly.
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The application window will be open until at least September 29, 2026. This opportunity will remain online based on business needs which may be before or after the specified date.
Applicants in the County of Los Angeles: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
This role may also be located in our Playa Vista, CA campus.
Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.
In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: San Francisco, CA, USA; Atlanta, GA, USA; Boulder, CO, USA; Chicago, IL, USA; Addison, TX, USA; Irvine, CA, USA; Los Angeles, CA, USA; San Diego, CA, USA; Seattle, WA, USA; Sunnyvale, CA, USA; Austin, TX, USA.
Minimum qualifications:
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 8 years of experience with software development using Python or similar coding languages.
- Experience deploying resources via Terraform or similar tools to automate the setup of agents, functions, or networking.
- Experience building full-stack applications that interact with enterprise IT infrastructures and developing external customer projects.
- Experience architecting AI systems on cloud platforms (e.g., Google Clloud Platform (GCP).
Preferred qualifications:
- Master’s degree or PhD in AI, Computer Science, or a related technical field.
- Experience implementing multi-agent systems using frameworks like ReAct and self-reflection.
- Experience debugging agent logic and optimizing tool selection, including tracing conversation identifications (IDs) across microservices to identify and resolve failures in real-time.
- Experience connecting agents to enterprise knowledge bases and optimizing retrieval-augmented Generation (RAG) chunking to prevent hallucinations.
- Track record of troubleshooting live, high-traffic systems during critical windows.
- Ability to travel up to 50% of the time.
About the job
As a Forward Deployed Engineer (FDE) in Applied AI, you will be the Agent Engineer and the primary driver for our customers' most critical AI initiatives. You will take initial conversational prototypes and transform them into production-ready solutions, owning the end-to-end engineering lifecycle, including the transition from art of the possible to real-world business value and scalable, secure AI systems. This is a high-travel, role focused on leading technical delivery for conversational AI pilots and establishing the first customer user journeys (CUJs) for our largest customers at their sites. You will have an understanding of software engineering, Machine Learning operations, and cloud infrastructure.It's an exciting time to join Google Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll excel by leveraging Google's brand credibility—a legacy built on inventing foundational technologies and proven at scale. We’ll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We’re a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era—the market is yours. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Serve as the lead developer for conversational AI and customer experience applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, model context protocol (MCP) servers) that drive measurable return on investment.
- Architect and code conversational flows that are functional, and optimized for the connective tissue between Google’s conversational AI products and customers’ live infrastructure, including APIs, legacy data silos, and security perimeters.
- Build high-performance evaluation pipelines and observability frameworks to optimize agentic workloads, focusing on reasoning loops, tool selection, and reducing latency while maintaining production-grade security and networking.
- Identify repeatable field patterns and technical friction points in Google’s Applied Artificial Intelligence (AAI) stack, converting them into reusable modules or product feature requests for Engineering teams.
- Co-build with customer engineering teams to instill Google-grade development best practices, ensuring project success and end-user adoption.
The application window will be open until at least September 29, 2026. This opportunity will remain online based on business needs which may be before or after the specified date.
Applicants in the County of Los Angeles: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
This role may also be located in our Playa Vista, CA campus.
Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.
In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: San Francisco, CA, USA; Atlanta, GA, USA; Boulder, CO, USA; Chicago, IL, USA; Addison, TX, USA; Irvine, CA, USA; Los Angeles, CA, USA; San Diego, CA, USA; Seattle, WA, USA; Sunnyvale, CA, USA; Austin, TX, USA.
Minimum qualifications:
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 8 years of experience with software development using Python or similar coding languages.
- Experience deploying resources via Terraform or similar tools to automate the setup of agents, functions, or networking.
- Experience building full-stack applications that interact with enterprise IT infrastructures and developing external customer projects.
- Experience architecting AI systems on cloud platforms (e.g., Google Clloud Platform (GCP).
Preferred qualifications:
- Master’s degree or PhD in AI, Computer Science, or a related technical field.
- Experience implementing multi-agent systems using frameworks like ReAct and self-reflection.
- Experience debugging agent logic and optimizing tool selection, including tracing conversation identifications (IDs) across microservices to identify and resolve failures in real-time.
- Experience connecting agents to enterprise knowledge bases and optimizing retrieval-augmented Generation (RAG) chunking to prevent hallucinations.
- Track record of troubleshooting live, high-traffic systems during critical windows.
- Ability to travel up to 50% of the time.
About the job
As a Forward Deployed Engineer (FDE) in Applied AI, you will be the Agent Engineer and the primary driver for our customers' most critical AI initiatives. You will take initial conversational prototypes and transform them into production-ready solutions, owning the end-to-end engineering lifecycle, including the transition from art of the possible to real-world business value and scalable, secure AI systems. This is a high-travel, role focused on leading technical delivery for conversational AI pilots and establishing the first customer user journeys (CUJs) for our largest customers at their sites. You will have an understanding of software engineering, Machine Learning operations, and cloud infrastructure.It's an exciting time to join Google Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll excel by leveraging Google's brand credibility—a legacy built on inventing foundational technologies and proven at scale. We’ll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We’re a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era—the market is yours. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Serve as the lead developer for conversational AI and customer experience applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, model context protocol (MCP) servers) that drive measurable return on investment.
- Architect and code conversational flows that are functional, and optimized for the connective tissue between Google’s conversational AI products and customers’ live infrastructure, including APIs, legacy data silos, and security perimeters.
- Build high-performance evaluation pipelines and observability frameworks to optimize agentic workloads, focusing on reasoning loops, tool selection, and reducing latency while maintaining production-grade security and networking.
- Identify repeatable field patterns and technical friction points in Google’s Applied Artificial Intelligence (AAI) stack, converting them into reusable modules or product feature requests for Engineering teams.
- Co-build with customer engineering teams to instill Google-grade development best practices, ensuring project success and end-user adoption.
See All 33 Applied AI Engineer Jobs in Texas
Find roles in Texas that match your experience and apply in just a few clicks.
Find Applied AI Engineer JobsApplied AI Engineer Jobs by City in Texas
Where Texas roles are concentrated, by current openings.
Applied AI Engineer Job Market in Texas
A snapshot from current Texas openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Fintech
- Technology & Software
- Banking & Financial Services
What Texas Employers Look For
The qualifications that appear most often in applied AI engineer jobs across Texas.
- Bachelor's or master's degree in computer science, machine learning, or a related engineering field
- Hands-on experience building and deploying production ML or deep learning models
- Proficiency in Python and at least one major ML framework such as PyTorch or TensorFlow
- Experience with cloud platforms including AWS, Azure, or Google Cloud for model deployment
- Familiarity with MLOps tooling, CI/CD pipelines, and model monitoring in production environments
- Strong communication skills for translating AI outputs into actionable insights for business stakeholders
Applied AI Engineer Jobs in Texas: Frequently Asked Questions
How do you become a applied ai engineer in Texas?
Applied AI engineering in Texas requires no state-issued license, so the path runs through education and demonstrated technical skill. Most Texas employers expect at least a bachelor's degree in computer science, data science, or a closely related field, with a master's degree preferred at mid-level and above. Building a portfolio of deployed models, contributing to open-source projects, and earning cloud certifications from AWS or Google Cloud are the credentials that move Texas applications forward.
How much do applied AI engineers make in Texas?
Applied AI engineers in Texas earn a median of about $132,150 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $82,600 for the lowest 10% to over $183,680 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire applied ai engineers in Texas?
Employers hiring applied ai engineers in Texas right now include SpaceX, Deloitte, and PressW, based on current listings on Migrate Mate as of September 2026. Texas's mix of Fortune 500 headquarters, defense contractors, and fast-growing technology firms creates a broad and consistent pipeline of applied AI roles across sectors.
Which Texas cities have the most applied ai engineer jobs?
Austin, Dallas, and Texas lead Texas for applied ai engineer openings. Austin's dense concentration of technology company headquarters and research offices drives the highest volume, while Dallas benefits from its large financial services and telecommunications employers, and Houston's energy sector and medical center institutions generate steady demand for applied AI talent.
Are there remote applied ai engineer jobs in Texas?
Yes, and more than most fields. About 78% of applied ai engineer openings tied to Texas are remote or hybrid as of September 2026, reflecting how much of this work centers on code, model training, and analysis rather than on-site equipment. Research, experimentation, and MLOps pipeline work are the areas most commonly offered as fully remote.
How can I get hired as a applied ai engineer in Texas with little or no experience?
The most realistic entry path is through a junior ML engineer or data engineer role at a Texas technology company or large enterprise. Employers like Dell Technologies, USAA, and Texas-based defense contractors run early-career associate programs and rotational technology tracks that accept candidates with strong academic projects in lieu of industry experience. A GitHub portfolio showing end-to-end model work, even on public datasets, and an AWS or Google Cloud associate certification consistently separate new applicants in Texas hiring pipelines.
Where can I find and apply to applied ai engineer jobs in Texas?
You can find and apply to applied ai engineer jobs in Texas on Migrate Mate, which lists current Texas openings across industries and experience levels. Find a role that fits and apply directly from the listing.
See All 33 Applied AI Engineer Jobs in Texas
Find roles in Texas that match your experience and apply in just a few clicks.
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