AI Engineer Jobs in Texas
AI Engineer jobs in Texas are among the most actively recruited technology roles in the country, with demand concentrated in enterprise software, defense and aerospace, energy technology, and financial services at levels from entry-level to principal. Austin, Dallas, and Houston lead hiring volume, and established employers such as Dell Technologies, Lockheed Martin, and ExxonMobil consistently staff ai engineer teams in the state. The most in-demand specialties are large language model development, MLOps and model deployment, and computer vision applied to industrial and energy systems. Find a role that fits below and apply directly.
Find AI Engineer JobsOverview
Showing 5 of 713+ AI Engineer jobs











INTRODUCTION
Imagine what you could do here. At Apple, new ideas have a way of becoming outstanding products, services, and customer experiences very quickly. Bring passion and dedication to your job, and there's no telling what you could accomplish.
Apple's Sales organization generates the revenue needed to fuel our ongoing development of products and services. This, in turn, enriches the lives of hundreds of millions of people around the world. We are, in many ways, the face of Apple to our largest customers.
Apple's US Decision Intelligence (DI) team is looking for a talented individual who is passionate about crafting, implementing, and operating AI solutions that have a direct and measurable impact on Apple Sales and its customers.
Description
We’re looking for a Senior AI Engineer with strong software development skills and a passion for applying LLMs and Agentic workflows to real-world business problems. You’ll be responsible for building, testing, and optimizing intelligent agents, retrieval pipelines, and embedded AI features across our sales data platforms.
Responsibilities
- Design, prototype, and productionize LLM-powered applications that combine structured data, unstructured knowledge, semantic layers, and internal business logic
- Build agentic AI systems that can retrieve context, reason across data sources, call tools and APIs, generate insights, and support business decision-making
- Partner with product, data science, design, engineering, and business stakeholders to translate ambiguous business problems into practical AI solutions
- Build modular APIs, SDKs, and micro-services to integrate LLMs, RAG pipelines, traditional ML models, data pipelines, and enterprise systems
- Design secure and reliable integrations between LLMs, internal APIs, databases, knowledge sources, and enterprise tools
- Partner closely with data science, engineering, and sales ops to embed context-aware intelligence in decision-making tools
- Lead technical decision-making on infrastructure components, embedding safety mechanisms (e.g., autonomy sliders, grounding checks, model monitoring)
- Build scalable pipelines for multi-modal agent input, memory, and semantic routing
- Collaborate closely with business teams to incorporate AI into their weekly cadences
- Balance fast experimentation with production readiness, ensuring AI capabilities are scalable, measurable, reliable, and maintainable
PREFERRED QUALIFICATIONS
- Hands-on experience building production-grade AI agents, including tool calling, routing, multi-step reasoning flows, agent handoffs, memory/session management, and human-in-the-loop patterns
- Ability to balance rapid prototyping with production readiness, especially when moving from proof-of-concept to scalable enterprise features
- Strong experience articulating and translating business questions into AI solutions
- Communicate results and insights effectively to partners and senior leaders, as well as both technical and non-technical audiences
- Sound communication skills - adept at messaging domain and technical content, at a level appropriate for the audience. Strong ability to gain trust with stakeholders and senior leadership
- Familiarity with embeddings, retrieval algorithms, knowledge graphs, vector databases, hybrid retrieval, reranking, and graph-based approaches to enterprise knowledge modeling
- Other complementary technologies for distributed systems architecture and asynchronous messaging, agent communication, and catching like RabbitMQ, Redis, and Valkey are preferred
- Advanced Degree (MS or Ph.D.) in Economics, Electrical Engineering, Statistics, Data Science, or a similar quantitative field is preferred
MINIMUM QUALIFICATIONS
- 10+ years of experience in ML, software engineering, or data science, with recent focus on Applied AI and LLMs
- Ability to lead development of AI projects from start to finish
- Proficiency in Python (FastAPI, LangChain, or similar frameworks), context engineering, and RESTful API design
- Hands-on experience with LLM APIs, embeddings, vector databases, and RAG workflows
- Solid grounding in data structures, async programming, and pipeline orchestration
- Experience with agent orchestration frameworks such as LangGraph, Google ADK, CrewAI, AutoGen, or similar frameworks
- Familiarity with Claude Code-style agentic engineering patterns, including subagents, hooks, MCP integrations, permissions, and session-based workflows
- Bias for action, curiosity, and a collaborative mindset
- Familiarity with telemetry and evaluation frameworks for AI agents
- Ability to design business-context layers that combine structured data, semantic definitions, user permissions, domain logic, and unstructured knowledge to produce grounded AI responses. Strong time management skills with the ability to collaborate across multiple teams
- Able to balance competing priorities, long-term projects, and ad hoc requirements
- Ability to work in a fast-paced, dynamic, constantly evolving business environment
- Comfortable with rapid prototyping, reproduction, and validation of research ideas
- We’re looking for someone with an eagerness and ability to learn new skills and solve dynamic problems in an encouraging and expansive environment
- B.S Degree in Computer Science/Engineering, or equivalent work experience
PAY & BENEFITS
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $212,000 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
See All 713+ AI Engineer Jobs in Texas
Find roles in Texas that match your experience and apply in just a few clicks.
Find AI Engineer JobsAI Engineer Jobs by City in Texas
Where Texas roles are concentrated, by current openings.
AI Engineer Job Market in Texas
A snapshot from current Texas openings, updated as new roles post.
Who's Hiring
- Apple84

- Shield AI56

- NVIDIA26

- PepsiCo19

- LTIMindtree18

Top Industries Hiring
- Technology & Software237
- Electronics & Hardware109
- Consulting & Professional Services90
- Aerospace & Defense54
- Banking & Financial Services44
What Texas Employers Look For
The qualifications that appear most often in AI engineer jobs across Texas.
- Bachelor's or master's degree in computer science, data science, or a related engineering field
- Hands-on experience building and deploying machine learning models in production environments
- Proficiency in Python and familiarity with frameworks such as TensorFlow, PyTorch, or JAX
- Experience with cloud platforms including AWS, Azure, or Google Cloud for model hosting
- Strong understanding of MLOps practices including CI/CD pipelines and model monitoring
- Ability to collaborate with cross-functional teams including data engineers and product managers
AI Engineer Jobs in Texas: Frequently Asked Questions
How do you become a ai engineer in Texas?
Texas does not require a state-issued license to work as an ai engineer, so the path runs through education and demonstrated technical skills. Most Texas employers expect at minimum a bachelor's degree in computer science, data science, or electrical engineering, with a master's degree competitive at larger companies like Dell, Boeing, or the major energy firms. Building a portfolio of deployed model projects and earning cloud certifications from AWS or Google strengthens applications considerably.
Which companies hire ai engineers in Texas?
Employers hiring ai engineers in Texas right now include Apple, Shield AI, and NVIDIA, based on current listings on Migrate Mate as of June 2026. Texas's concentration of defense contractors, energy majors, and large enterprise technology campuses means ai engineer openings appear across a wider range of industries than most states.
Which Texas cities have the most ai engineer jobs?
Austin, Dallas, and Houston hold the most ai engineer openings in Texas. Austin's dense technology startup and corporate campus ecosystem drives the bulk of software-focused roles, Dallas anchors financial services and telecom AI hiring, and Houston's energy sector generates strong demand for ai engineers working on industrial automation and predictive maintenance applications.
Are there remote ai engineer jobs in Texas?
Yes, and more than most fields, since ai engineering work is largely code, experimentation, and model evaluation that transfers well to remote environments. About 19% of ai engineer openings tied to Texas are remote or hybrid as of June 2026, reflecting how broadly distributed this talent pool has become. Roles focused on research, NLP, and model fine-tuning tend to be the most remote-accessible, while positions involving on-premise GPU infrastructure or classified defense work are typically on-site.
How can I get hired as a ai engineer in Texas with little or no experience?
The most realistic entry path is through a machine learning engineering or data science associate role, which several large Texas employers use as a structured on-ramp. Companies like Texas Instruments and Raytheon run rotational engineering programs that include AI and data tracks, and energy firms including Chevron and ExxonMobil hire data science associates at Texas campuses. Building two or three end-to-end project deployments on GitHub, earning an AWS or Google Cloud machine learning certification, and targeting these associate-level postings gives candidates without prior industry experience a credible foundation.
Where can I find and apply to ai engineer jobs in Texas?
You can find and apply to ai engineer jobs in Texas on Migrate Mate, which lists current Texas openings from employers actively hiring in the state. Find the roles that fit your background and apply directly through each listing.
See All 713+ AI Engineer Jobs in Texas
Find roles in Texas that match your experience and apply in just a few clicks.
Find AI Engineer Jobs