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Mistral Jobs in Arizona (NOW HIRING)

OmegaHires

Gen AI Engineer with Python

Phoenix, AZ · On-site

Experience integrating LLMs including OpenAI, Azure OpenAI, Gemini, Claude, Llama, or Mistral. Strong knowledge of Prompt Engineering, AI orchestration, and tool/function calling. Experience ...

OmegaHires

Lead Gen AI Engineer with Python

Phoenix, AZ · On-site

$139K - $170K/yr

Experience integrating LLMs including OpenAI, Azure OpenAI, Gemini, Claude, Llama, or Mistral. Strong knowledge of Prompt Engineering, AI orchestration, and tool/function calling. Experience ...

OmegaHires

Lead Gen AI Engineer

Phoenix, AZ · On-site

$101K - $134K/yr

... Llama, or Mistral. - Strong knowledge of Prompt Engineering, AI orchestration, and tool/function calling. - Experience developing APIs using FastAPI, Flask, or Django. - Experience with Docker ...

Pwc

AI Engineer

Phoenix, AZ · On-site

$50K - $112K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... Mistral, and Gemma, for local and cloud deployment using quantization, inference acceleration, and model-routing techniques - Designing agent harnesses and implementing context engineering, memory ...

All JobsMistral JobsMistral Jobs in Arizona

Mistral information

See Arizona salary details

$14K

$224.9K

$360.6K

How much do mistral jobs pay per year?

As of Aug 18, 2026, the average yearly pay for mistral in Arizona is $224,860.00, according to ZipRecruiter salary data. Most workers in this role earn between $186,400.00 and $279,600.00 per year, depending on experience, location, and employer.

What is a Mistral?

Mistral jobs refer to roles related to Mistral, which can indicate either a workflow orchestration service in IT or positions at Mistral AI, a company specializing in artificial intelligence and large language models. In the context of workflow orchestration, Mistral jobs involve creating, managing, and monitoring automated workflows, often in cloud or DevOps environments. At Mistral AI, jobs can include research, software engineering, and AI model development. Responsibilities usually focus on building scalable, efficient systems or advancing state-of-the-art machine learning technologies.

What are the key skills and qualifications needed to thrive as a Mistral engineer?

To thrive as a Mistral Engineer, you need a solid background in software engineering, machine learning, and natural language processing, often supported by a degree in computer science or a related field. Familiarity with frameworks like PyTorch or TensorFlow, experience with distributed systems, and version control tools such as Git are typically required. Strong problem-solving skills, collaboration, and adaptability help individuals excel in this dynamic, innovative environment. These competencies are crucial for driving advancements in AI technology and delivering robust, scalable solutions.

What are some typical challenges faced by Mistral engineers when integrating AI models into production environments?

Mistral engineers often encounter challenges such as ensuring model scalability, managing latency, and maintaining robust security when deploying AI models into production. They must frequently collaborate with data scientists, DevOps, and product teams to fine-tune models, monitor real-world performance, and address unexpected behavior. Staying updated with rapid advancements in machine learning frameworks and cloud infrastructure is also crucial. Effective communication and agile problem-solving are key to overcoming these hurdles and delivering reliable AI solutions.

What is the difference between Mistral vs Data Scientist?

AspectMistralData Scientist
Required CredentialsTypically requires a background in engineering, physics, or related fields; certifications are optionalRequires a degree in computer science, statistics, or related fields; certifications like Certified Data Scientist are common
Work EnvironmentOften works in research labs, tech companies, or startups focusing on AI and machine learningWorks in various industries including finance, healthcare, and tech, analyzing data to inform decisions
Employer & Industry UsageUsed mainly in AI research and development, especially in natural language processingWidely used across industries for data analysis, predictive modeling, and business insights

While both Mistral and Data Scientists work with advanced technology, Mistral typically focuses on AI research and development, often requiring a strong engineering background. Data Scientists analyze data to generate insights across industries. The roles overlap in technical skills but differ in focus and application.

What is it like to work at Mistral?

Working as a Mistral involves engaging in roles that may require technical skills, teamwork, and adherence to safety protocols. Employees often work in collaborative environments with a focus on efficiency and quality, and may need to be adaptable to changing project demands or schedules.

What are popular job titles related to Mistral jobs in Arizona?

For Mistral jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Mistral jobs in Arizona look for?

The top searched job categories for Mistral jobs in Arizona are:

What cities in Arizona are hiring for Mistral jobs?

Cities in Arizona with the most Mistral job openings:

Mistral jobs near you
Infographic showing various Mistral job openings in Arizona as of August 2026, with employment types broken down into 94% Full Time, 2% Part Time, and 4% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $224,860 per year, or $108.1 per hour.

Gen AI Engineer with Python

OmegaHires

Phoenix, AZ • On-site

Contractor

Posted 4 days ago

Job description

Gen AI Engineer with Python
Job Description:We are looking for a Gen AI Engineer with strong expertise in Python, Generative AI, Retrieval-Augmented Generation (RAG), and Agentic AI to lead the design and development of enterprise AI solutions. The ideal candidate will have hands-on experience in preparing and engineering enterprise data for AI use cases, building scalable RAG pipelines, implementing autonomous AI agents, and integrating Large Language Models (LLMs) into production environments.
This is a hands-on technical leadership role requiring deep knowledge of AI architecture, data preparation, prompt engineering, vector databases, and modern AI frameworks.
Required Skills
8+ years of software development experience with Python.
3+ years of hands-on experience delivering Generative AI solutions.
Strong expertise in Retrieval-Augmented Generation (RAG) architecture and implementation.
Hands-on experience building Agentic AI solutions using LangGraph, CrewAI, AutoGen, LangChain, LlamaIndex, or Semantic Kernel.
Experience preparing, processing, and engineering structured and unstructured enterprise data for AI use cases.
Strong understanding of document ingestion, chunking strategies, embeddings, metadata enrichment, and vector search.
Experience with Vector Databases such as Pinecone, FAISS, ChromaDB, Weaviate, or Milvus.
Experience integrating LLMs including OpenAI, Azure OpenAI, Gemini, Claude, Llama, or Mistral.
Strong knowledge of Prompt Engineering, AI orchestration, and tool/function calling.
Experience developing APIs using FastAPI, Flask, or Django.
Experience with Docker, Kubernetes, Git, CI/CD, and cloud platforms (AWS, Azure, or GCP).
Preferred Skills
Experience with AI evaluation frameworks, observability, and LLMOps.
Knowledge of MLOps and AI model deployment.
Experience with Databricks, Snowflake, or enterprise data platforms.
Familiarity with knowledge graphs and enterprise search solutions.

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