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Llmops Jobs in Texas (NOW HIRING)

Lead AI/ML Platform Engineer

Plano, TX · On-site

$98K - $129K/yr

You will help enable secure, production-ready MLOps and LLMOps infrastructure that supports model training, inference, orchestration, and retrieval-augmented generation. The Lead AI/ML Platform ...

Senior AI/ML Platform Engineer

Plano, TX · On-site

$100K - $137K/yr

Implement and operate MLOps and LLMOps capabilities including model training workflows, deployment pipelines, monitoring, and rollback support. * Build and optimize containerized and GPU-enabled ...

Agentic AI Engineer

Dallas, TX · On-site

$120K - $140K/yr

Apply LLMOps best practices including prompt engineering, prompt versioning, evaluation, monitoring, logging, observability, and performance optimization. * Define and execute testing strategies for ...

Agentic AI Engineer

Dallas, TX · On-site

$150 - $200/hr

Apply LLMOps best practices including prompt engineering, prompt versioning, evaluation, monitoring, logging, observability, and performance optimization. * Define and execute testing strategies for ...

Agentic AI Engineer

Dallas, TX · On-site

$150 - $210/hr

Apply LLMOps best practices including prompt engineering, prompt versioning, evaluation, monitoring, logging, observability, and performance optimization. * Define and execute testing strategies for ...

AI Architect

Irving, TX · On-site

$150K - $201K/yr

Implement observability and LLMOps practices including monitoring, evaluation, drift detection, performance tuning, and telemetry using Azure Monitor and Application Insights. Collaborate with cross ...

Implement MLOps and LLMOps best practices for model deployment, monitoring, governance, and lifecycle management. * Ensure AI solutions comply with enterprise security, responsible AI, and regulatory ...

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Showing results 1-20

Llmops information

What is the difference between Llmops vs Data Scientist?

AspectLlmopsData Scientist
Required credentialsKnowledge of machine learning, AI frameworks, cloud platformsStatistics, programming, data analysis skills
Work environmentAI/ML teams, cloud environments, deployment pipelinesData analysis, modeling, reporting in various industries
Employer usageTech companies, AI startups, research labsFinance, healthcare, tech, retail

While both roles involve working with data and machine learning, Llmops focuses on deploying and maintaining large language models in production environments, requiring expertise in AI infrastructure. Data Scientists primarily analyze data, build models, and generate insights. Llmops professionals ensure models operate efficiently at scale, whereas Data Scientists develop the models and interpret results.

What cities in Texas are hiring for Llmops jobs?

Cities in Texas with the most Llmops job openings:

Infographic showing various Llmops job openings in Texas as of August 2026, with employment types broken down into 81% Full Time, 2% Temporary, and 17% Contract. Highlights an 82% In-person, 3% Hybrid, and 15% Remote job distribution.

Senior Technology Architect | Artificial Intelligence | Artificial Intelligence - ALL

Spruce Infotech

Irving, TX • On-site

$62.50 - $83.50/hr

Full-time

Re-posted 4 days ago


Job description

Job Title: GEN AI engineer & Agentic AI Engineer
Work Location : Dallas, or Charlotte Infosys
Vendor Rate: XXX/hour
Contract duration: 6-12 months depending performance
Target Start Date: 01-July 2026
Does this position require Visa independent candidates only? YES
Interview Process (Is face to face required?) Yes
Mandatory (Either in Dallas or in Charlotte at Client office)
Job Details:
Must Have Skills
GEN AI, Agentic AI Cortex AI,, ML Ops,Python, ML, Data Science, RAG,LLM
Nice to have skills
GCP, Prompt Engineering
We are seeking a highly skilled Generative AI Engineer with a strong Python background to design, develop, and deploy cutting-edge AI solutions. The ideal candidate will have hands-on experience with Large Language Models (LLMs), prompt engineering, and Gen AI frameworks, along with expertise in building scalable AI applications. Experience in Developing Agentic AI solutions.
Key Responsibilities:
Design and implement Generative AI models for text, image, or multimodal applications.
Develop prompt engineering strategies and embedding-based retrieval systems.
Integrate Gen AI capabilities into web applications and enterprise workflows.
Build agentic AI applications with context engineering and MCP tools. Required Skills & Qualifications:
10+ years of hands-on experience in AI, Data science, ML, GEN AI.
Strong hands on experience designing and deploying Retrieval-Augmented Generation (RAG) pipelines
Strong hands-on experience with RAG pipelines and vector databases
Extensive experience with LangChain, LangGraph, CrewAI, multi-agent orchestration
Strong MLOps / LLMOps experience with CI/CD automation
Experience across AWS (SageMaker, Lambda, EKS, S3) and GCP (Vertex AI)
API & microservices development using FastAPI, REST, Docker, Kubernetes
• Strong Python proficiency with PyTorch / TensorFlow
Strong MLOps/LLMOps experience with CI/CD automation,
Extensive experience with LangChain, LangGraph, and agentic AI patterns including routing, memory, multi-agent orchestration, guardrails, and failure recovery.
Experience in Developing microservices and API development using FastAPI, REST APIs, Pydantic/JSON schemas, Docker, and Kubernetes for low-latency serving.
Strong Hands-on experience with vector databases and semantic search technologies including Pinecone, FAISS, ChromaDB, and embedding lifecycle management
Strong proficiency in Python and AI/ML frameworks (PyTorch, TensorFlow).
Hands on experience using session and memory for building multi-agent systems along with using MCP tools.
Hands-on experience with LLMs, transformers, and Hugging Face ecosystem.
Knowledge and experience with vector databases and RAG technique for semantic search.
Familiarity with cloud AI services (AWS SageMaker, Azure OpenAI, GCP Vertex AI).
Understanding of MLOps practices for scalable AI deployment.
Strong experience in working with LLM fine-tuning with LoRA, QLoRA, PEFT,
Strong experience in Architected advanced RAG systems using Pinecone, FAISS, Weaviate, Chroma, hybrid retrieval, and custom embeddings,
Strong experience in Designing end-to-end LLMOps/MLOps pipelines using MLflow, DVC, SageMaker Pipelines, Vertex AI Pipelines, and GitHub Actions
Experience in using cloud-native AI systems on AWS (SageMaker, Lambda, EKS, EC2, Step Functions, S3, Glue) and GCP Vertex AI, supporting high-volume inference and secure enterprise operations
Experience in developing multi-agent orchestration workflows using LangGraph and CrewAI for tool-calling, validation agents, automated reasoning, and workflow supervision
Minimum years of experience
>10 years
Certifications Needed :NA
Top 3 responsibilities you would expect the Subcon to shoulder and execute
Strong experience in Developing Agents, MCP, Tools, GEN AI, LLM, RAG,ML, DL, Agentic AI ML Ops, LLMOps, Cloud platform,Model servicing optimization, Python
Strong communication skills
Strong programming skills
Interview Process (Is face to face required?) Yes
Mandatory (Either in Dallas or in Charlotte at Client office)
Any additional information you would like to share about the project specs/ nature of work
na
Project Code: WF GEN AI PLATFORM SUPPORT CTO