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Generative Ai Developer Jobs in Texas (NOW HIRING)

SWBC

AI Engineer

San Antonio, TX · On-site

AWS Certified Generative AI Developer - Professional * Experience training, fine-tuning, or hosting open-source large language models internally. * Experience with AWS Bedrock and Bedrock AgentCore.

Swbc

AI Engineer

San Antonio, TX

AWS Certified Generative AI Developer - Professional * Experience training, fine-tuning, or hosting open-source large language models internally. * Experience with AWS Bedrock and Bedrock AgentCore.

myDNA, Inc.

Senior AI Developer

Houston, TX · On-site

$52 - $68.75/hr

You will integrate generative-AI features into our products and internal platforms, combine ... NET and SQL engineering teams responsible for backend services and data-layer integration with AI ...

Droisys

Generative AI LangGraph experience

Plano, TX · On-site

Generative AI Engineer with LangGraph experience Plano, TX- Fully Onsite from Day-1 Core Technical Skills: * Python Programming: Advanced proficiency in Python, including experience with asynchronous ...

COVET IT INC

Junior/Intern Gen AI Developer

Dallas, TX · On-site

$19 - $25/hr

Generative AI and Large Language Models (LLMs) * Agentic AI and Multi-Agent Systems * RAG Architecture and Semantic Search * Prompt Engineering * Fine-Tuning and Model Evaluation * Custom ML Model ...

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How much do generative ai developer jobs pay per hour?

As of Jul 25, 2026, the average hourly pay for generative ai developer in Texas is $42.19, according to ZipRecruiter salary data. Most workers in this role earn between $21.97 and $51.06 per hour, depending on experience, location, and employer.

What are some common challenges faced by Generative AI Developers when deploying models in production environments?

Generative AI Developers often encounter challenges such as ensuring model reliability, managing computational resource requirements, and addressing ethical considerations like data bias or content safety. Deploying generative models at scale requires robust monitoring to detect unexpected outputs or model drift, and collaboration with data engineers and product teams to optimize performance. Staying up-to-date with evolving frameworks and best practices is essential, as production environments demand both technical rigor and adaptability to new AI advancements.

What are the key skills and qualifications needed to thrive as a Generative AI Developer, and why are they important?

To thrive as a Generative AI Developer, you need strong programming skills (especially in Python), a deep understanding of machine learning concepts, and an advanced degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and experience with cloud platforms or model deployment tools are typically required. Creative problem-solving, adaptability, and effective collaboration are standout soft skills in this evolving field. These abilities are crucial to design, implement, and refine generative models that solve real-world problems and drive innovation.

Is generative AI a good career?

Generative AI is a rapidly growing field with high demand for skilled developers who can create and optimize AI models using tools like deep learning frameworks. Careers in this area often require knowledge of machine learning, programming, and data handling, offering opportunities in tech companies, research, and startups. The field provides competitive salaries and continuous learning opportunities due to its evolving nature.

What is the difference between Generative Ai Developer vs Machine Learning Engineer?

AspectGenerative Ai DeveloperMachine Learning Engineer
CredentialsBachelor's or higher in CS, AI, or related fields; experience with deep learning frameworksBachelor's or higher in CS, Data Science, or related fields; strong programming skills
Work EnvironmentDevelops AI models for content creation, chatbots, and creative applicationsBuilds and deploys ML models for various data-driven solutions across industries
Industry UsageTech, entertainment, marketing, and creative sectorsFinance, healthcare, tech, and e-commerce sectors

While both roles involve AI and machine learning, Generative Ai Developers focus on creating models that generate content, such as images or text, whereas Machine Learning Engineers develop broader ML solutions for diverse applications. The roles often overlap but differ mainly in their specific focus areas and use cases.

What is the salary of a generative AI developer?

The salary of a generative AI developer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and skill set. Senior developers with expertise in machine learning frameworks and deep learning may earn higher compensation, especially in tech hubs or companies with advanced AI projects.

What does a generative AI developer do?

A generative AI developer designs and builds algorithms that enable machines to create content such as text, images, or audio. They work with machine learning frameworks, train models on large datasets, and optimize algorithms for performance and accuracy, often using tools like Python and TensorFlow or PyTorch.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence development, such as a senior Generative AI Developer or AI research lead, often involving advanced skills in machine learning, deep learning, and large language models. These roles usually require extensive experience, specialized knowledge, and may include responsibilities like designing AI systems, managing teams, or overseeing AI strategy in organizations with competitive compensation packages. Such salaries are common in top tech companies or specialized AI firms for highly skilled professionals.

What is a Generative AI Developer?

A Generative AI Developer is a technology professional who specializes in designing, building, and deploying artificial intelligence systems that can create new content, such as text, images, audio, or code. They work with advanced machine learning models, like generative adversarial networks (GANs) or large language models, to enable computers to produce original outputs. These developers often collaborate with data scientists, researchers, and product teams to integrate AI-generated content into software applications and business solutions.
What are popular job titles related to Generative Ai Developer jobs in Texas? For Generative Ai Developer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Generative Ai Developer jobs in Texas look for? The top searched job categories for Generative Ai Developer jobs in Texas are:
What cities in Texas are hiring for Generative Ai Developer jobs? Cities in Texas with the most Generative Ai Developer job openings:
Generative Ai Developer jobs near you
Infographic showing various Generative Ai Developer job openings in Texas as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 64% Physical, 3% Hybrid, and 33% Remote job distribution, with an average salary of $87,761 per year, or $42.2 per hour.
AI Engineer

AI Engineer

SWBC

San Antonio, TX • On-site

Full-time

Medical, Retirement

Posted 23 days ago

SWBC rating

6.5

Company rating: 6.5 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

Job description

SWBC is seeking a talented individual to join our growing AI team as an AI Engineer. This role is responsible for designing, developing, and deploying AI-powered solutions that drive operational improvements and business outcomes across the organization. The ideal candidate will have hands-on experience with agentic AI systems, large language models (LLMs), prompt engineering, and production-ready AI applications within a security-conscious and regulated environment.
Why you'll love this role:
As an AI Engineer, you will play a key role in helping SWBC accelerate its AI initiatives by building and deploying intelligent solutions that solve real business challenges. You'll work with emerging technologies, including agentic AI frameworks, generative AI models, and AWS AI services, while partnering with business and technology teams to deliver measurable outcomes.
This is an opportunity to work in a fast-moving environment where ideas quickly move from concept to production. If you enjoy building, experimenting, and implementing AI solutions that create operational efficiencies and business value, this role offers the chance to make a meaningful impact while helping shape SWBC's AI capabilities.
Essential duties include the following:
  • Design, develop, and deploy AI-powered applications and agentic AI solutions that support business and operational objectives.
  • Build, test, and optimize AI workflows utilizing foundation models, open-source LLMs, and internally trained models.
  • Develop and maintain AI agents, APIs, and supporting services that enable scalable and secure AI operations.
  • Implement retrieval-augmented generation (RAG), vector database integrations, prompt engineering techniques, and agent-to-agent communication patterns.
  • Utilize frameworks such as LangChain, LangGraph, Strands, and AWS Bedrock AgentCore to develop enterprise AI solutions.
  • Deploy AI and machine learning models into production environments while ensuring reliability, scalability, and performance.
  • Partner with cross-functional stakeholders to evaluate business use cases and translate requirements into AI-driven solutions.
  • Develop and support data pipelines that enable model training, inference, and AI application performance.
  • Ensure AI solutions adhere to Responsible AI principles, security standards, governance requirements, and regulatory compliance expectations.
  • Contribute to the evolution of SWBC's AI architecture as the organization continues to expand and mature its AI platform capabilities.
  • Document solution architecture, workflows, models, and technical processes to support operational excellence and knowledge sharing.
  • Continuously evaluate emerging AI technologies, models, and frameworks to identify opportunities for innovation and business improvement.

Serious candidates will possess the minimum qualifications:
  • Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
  • Minimum of three (3) years of experience developing AI, machine learning, or generative AI solutions in a professional environment.
  • Hands-on experience developing and deploying solutions using Python.
  • Experience building and implementing agentic AI systems and AI-powered workflows.
  • Working knowledge of large language models (LLMs), foundation models, prompt engineering, and generative AI concepts.
  • Experience leveraging both pre-trained models and custom-trained AI models.
  • Experience developing APIs and integrating AI services into enterprise applications.
  • Understanding of vector databases, retrieval-augmented generation (RAG), fine-tuning approaches, and model deployment practices.
  • Experience working within AWS cloud environments and AWS AI services.
  • Knowledge of data pipelines and how they support AI and machine learning workflows.
  • Experience operating within a regulated environment with an understanding of security, governance, and Responsible AI principles.
  • Strong problem-solving skills with the ability to execute in a fast-paced environment and deliver solutions quickly.
  • Strong communication and collaboration skills with the ability to work effectively across business and technical teams.

Preferred Skills:
  • AWS Certified Machine Learning Engineer - Associate certification.
  • AWS Certified Generative AI Developer - Professional
  • Experience training, fine-tuning, or hosting open-source large language models internally.
  • Experience with AWS Bedrock and Bedrock AgentCore.
  • Experience with LangChain, LangGraph, and Strands frameworks.
  • Familiarity with Model Context Protocol (MCP) and agent-to-agent communication protocols.
  • Experience with C# development.
  • Experience supporting AI solutions through production deployments and ongoing optimization.
  • Exposure to MLOps practices and AI operationalization.

SWBC offers*:
  • Competitive overall compensation package
  • Work/Life balance
  • Employee engagement activities and recognition awards
  • Years of Service awards
  • Career enhancement and growth opportunities
  • Leadership Academy and Mentor Program
  • Continuing education and career certifications
  • Variety of healthcare coverage options
  • Traditional and Roth 401(k) retirement plans
  • Lucrative Wellness Program

*Based upon employee eligibility
Additional Information:
SWBC is a Substance-Free Workplace and requires pre-employment drug testing.
Please note, SWBC does not hire tobacco users as allowed by law.
To learn more about SWBC, visit our website at www.SWBC.com. If interested, please click the appropriate apply button.

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