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Generative Ai Consultant Jobs in Spring, TX (NOW HIRING)

Apetan Consulting llc

Generative AI Engineer

Houston, TX · On-site

$55 - $60/hr

Generative AI Engineer Work Location: Houston, TX Duration: 6-12 Months Contract Work Mode: Onsite from Day 1 Pay Rate Range: $50/hr. - $60/hr. on C2C Interview: Face to Face Interview is Mandatory ...

New

Resource Consulting Services

AI Architect IV

Houston, TX · On-site

$60.75 - $79/hr

AI & Generative AI Solutions * Design and implement AI-enabled business capabilities using Gemini Enterprise for CX, Azure AI Services and Azure OpenAI. * Develop Generative AI solutions including ...

New

SIA

AI Transformation Manager

Houston, TX

Mentor junior consultants and contribute to ETI practice development Evaluate & Guide AI Tool Adoption * Maintain working knowledge of Generative AI, AI agents, copilots, and automation platforms so ...

Sia

AI Transformation Manager

Houston, TX · On-site

Mentor junior consultants and contribute to ETI practice development Evaluate & Guide AI Tool Adoption * Maintain working knowledge of Generative AI, AI agents, copilots, and automation platforms so ...

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How much do generative ai consultant jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for generative ai consultant in Spring, TX is $36.98, according to ZipRecruiter salary data. Most workers in this role earn between $26.11 and $44.09 per hour, depending on experience, location, and employer.

What is a generative AI consultant?

A Generative AI Consultant helps businesses implement and optimize AI-driven solutions using generative models like GPT, DALL·E, or other advanced AI technologies. They assess client needs, recommend AI strategies, and support the integration of AI tools into workflows. Their role often includes model fine-tuning, prompt engineering, and ensuring ethical AI use. Additionally, they provide training and best practices to maximize AI's effectiveness while mitigating risks.

What are the typical daily responsibilities of a generative AI consultant?

A Generative AI Consultant’s daily responsibilities often include meeting with clients to assess their needs, designing and prototyping AI models, and collaborating with cross-functional teams to deploy solutions. You may spend time analyzing data, fine-tuning models, and presenting technical findings in an accessible way to both technical and non-technical stakeholders. Staying current with emerging advancements in generative AI and regularly evaluating the performance of deployed models are also key parts of the role. This position typically offers a dynamic mix of hands-on technical tasks and strategic client interactions, enabling you to see projects from concept to implementation.

What are the key skills and qualifications needed to thrive as a generative AI consultant?

To thrive as a Generative AI Consultant, you need strong expertise in machine learning, deep learning, and natural language processing, often supported by an advanced degree in computer science or a related field. Familiarity with frameworks and tools such as TensorFlow, PyTorch, Hugging Face libraries, and cloud platforms is typically required, along with relevant certifications like Google Cloud AI or AWS Machine Learning. Excellent problem-solving, communication, and client management skills help build rapport and translate technical concepts into actionable business solutions. These abilities are crucial for designing impactful AI solutions, effectively collaborating with stakeholders, and ensuring successful project outcomes.

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Generative Ai Consultant jobs near you

Generative AI Engineer

Apetan Consulting llc

Houston, TX • On-site

$55 - $60/hr

Contractor

Posted 2 days ago

New

Job description

Title: Generative AI Engineer
Work Location: Houston, TX 
Duration: 6-12 Months Contract
Work Mode: Onsite from Day 1
Pay Rate Range: $50/hr. - $60/hr. on C2C
Interview: Face to Face Interview is Mandatory
 
If you've been building software for a few years, you've picked up real engineering instincts, and you're the person on your team who's already experimenting with agents and LLMs on the side — this is a chance to do that work for real, at enterprise scale, on production systems that matter.
 
What you will do:
Build agentic features, hands-on. Work alongside senior engineers to design and ship AI-powered remediation capabilities: agent workflows, retrieval pipelines, evaluation loops.
Write production code daily. Java/Spring Boot microservices and AI integrations on AWS.
Learn the full lifecycle. From an idea in a design doc to something running in production, instrumented, monitored, and improved based on real usage.
Bring fresh eyes. You're closer to the newest models, frameworks, and techniques than engineers who've been heads-down in one stack for a decade — we want that perspective in the room, not just deference to seniority.
Grow fast. Work directly with senior engineers who'll push your technical depth, and take on more ownership as you earn it.
 
Our stack
Java / Spring Boot microservices on AWS (Lambda, SQS, SNS, IAM, CloudWatch). 
AI Stack: AWS Bedrock and AgentCore, MCP for tool integration, RAG pipelines with vector and graph-based retrieval, LLM-as-judge evaluation. Some Python and Go at the edges. You won't know all of this — we're more interested in how fast you pick things up than what's already on your resume.
 
What you will bring:
4+ years building software professionally — you've shipped real features, not just coursework or side projects, and you understand what "production" demands.
Genuine curiosity about AI/agentic systems — you've built something with LLMs or agents, even outside of work: a side project, a hackathon entry, an experiment that didn't ship. We want to hear about it.
Solid engineering fundamentals — distributed systems basics, APIs, cloud infrastructure (AWS). You need to know what good code and good design look like.
You experiment and iterate ideas quickly and bring new perspectives 
 
Nice to have
Experience with multiple LLM APIs or agent frameworks
Python or Go 
POCs using AI for coding, automation, or data work 
Contributions to open source AI/ML tooling.