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Crewai Jobs in Arizona (NOW HIRING)

Practical knowledge of model orchestration frameworks (e.g., LangChain, LlamaIndex, CrewAI), Familiarity with vector databases Experience with cloud platforms (AWS, Azure AI, Google Cloud Vertex AI ...

New

Experience with agentic AI frameworks or orchestration tools, such as LangChain, AutoGen, CrewAI, or comparable technologies. Hands-on experience with SQL and data manipulation. Working knowledge of ...

LangChain, LangGraph, AutoGen, or CrewAI * Exposure to APIs, cloud platforms (AWS, Azure, GCP), Docker, Kubernetes, and vector databases * MLOps/data tools: MLflow, Kubeflow, Argo Workflows, Kafka ...

AI & Machine Learning Engineer

Phoenix, AZ · On-site

$96K - $132K/yr

... CrewAI AI Agents, MCP, Prompt Engineering, Function Calling RAG solutions and Vector Databases Microsoft Fabric, Azure Data Factory, Azure SQL TensorFlow, PyTorch, Scikit-learn, MLflow Epic Clarity ...

AI & Machine Learning Engineer

Phoenix, AZ · On-site

$96K - $132K/yr

... CrewAI AI Agents, MCP, Prompt Engineering, Function Calling RAG solutions and Vector Databases Microsoft Fabric, Azure Data Factory, Azure SQL TensorFlow, PyTorch, Scikit-learn, MLflow Epic Clarity ...

... CrewAI AI Agents, MCP, Prompt Engineering, Function Calling RAG solutions and Vector Databases Microsoft Fabric, Azure Data Factory, Azure SQL TensorFlow, PyTorch, Scikit-learn, MLflow Epic Clarity ...

AI Engineer

Phoenix, AZ · On-site

$120 - $180/hr

... CrewAI, AutoGen or similar agent frameworks * Proven API integration work with OpenAI or Anthropic (function calling, tool use, streaming) * Strong understanding of REST APIs, webhooks and basic ...

... CrewAI AI Agents, MCP, Prompt Engineering, Function Calling RAG solutions and Vector Databases Microsoft Fabric, Azure Data Factory, Azure SQL TensorFlow, PyTorch, Scikit-learn, MLflow Epic Clarity ...

AI & Machine Learning Engineer

Chandler, AZ · On-site

$100K - $110K/yr

LangChain, LangGraph, Semantic Kernel, CrewAI * AI Agents, MCP, Prompt Engineering, Function Calling * RAG solutions and Vector Databases * Microsoft Fabric, Azure Data Factory, Azure SQL

Lead AI Engineer

Phoenix, AZ · On-site

$99K - $131K/yr

Agent and orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or CrewAI, with strong judgment about when to use frameworks versus building lighter-weight primitives * Model-level ...

Lead AI Engineer

Phoenix, AZ · On-site

$147 - $202/hr

Experience with agent frameworks or orchestration patterns such as OpenAI Agents SDK, LangChain, LangGraph, LlamaIndex, MCP, AutoGen, CrewAI, n8n, or comparable platforms. * Experience with Autodesk ...

Experience with agent frameworks or orchestration patterns such as OpenAI Agents SDK, LangChain, LangGraph, LlamaIndex, MCP, AutoGen, CrewAI, n8n, or comparable platforms. * Experience with Autodesk ...

Crewai information

What is a crewAI?

Crewai is not a traditional job title but rather a term related to CrewAI, an open-source framework that enables the creation and orchestration of collaborative AI agent teams to solve complex tasks. People working with Crewai typically build, configure, or manage multi-agent systems using this framework, often in tech or AI development roles. These professionals leverage agents—autonomous programs—to collaborate, communicate, and achieve shared objectives, streamlining workflows and automating sophisticated processes. Crewai experts are usually skilled in programming, artificial intelligence, and software integration.

What are the key skills and qualifications needed to thrive as a crewAI engineer, and why are they important?

To thrive as a Crew AI Engineer, you need a strong background in computer science, AI/ML algorithms, and proficiency in programming languages like Python or Java, often supported by a relevant degree. Experience with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms, and possibly certifications like AWS Certified Machine Learning are typical requirements. Excellent problem-solving skills, teamwork, and adaptability help you stand out in this fast-evolving field. These skills ensure you can design, implement, and maintain robust AI systems that enhance team productivity and drive innovation.

What are some common challenges faced when coordinating tasks within a crewAI team, and how can they be effectively managed?

Crewai team members often work in dynamic, cross-functional groups, which requires effective communication and adaptability. Common challenges include aligning schedules across different time zones, ensuring clear task delegation, and maintaining consistent progress updates. These challenges can be managed by using collaborative project management tools, setting regular check-ins, and fostering a transparent team culture. Open communication and proactive problem-solving help ensure everyone stays informed and engaged.

What cities in Arizona are hiring for Crewai jobs?

Cities in Arizona with the most Crewai job openings:

Infographic showing various Crewai job openings in Arizona as of August 2026, with employment types broken down into 63% Full Time, and 37% Contract. Highlights an 93% In-person, and 7% Remote job distribution.

AI Engineer

Phoenix, AZ

Contractor

Posted 3 days ago

New


Job description

AI Engineer - Agentic AI, Node Js
Typescript and Python, Gen AI, Agentic AI . Client is not considering candidates who do not have experience on this.
Technical Skills:
6+ years of experience building large-scale distributed systems + strong experience with LLM systems, agentic workflows or advanced ML infrastructure, async processing, queues, and streaming systems
Experience working on Typescript and Python, Gen AI, Agentic AI
Advanced proficiency in Python, Hands-on experience with PyTorch, TensorFlow, Hugging Face.
Practical knowledge of model orchestration frameworks (e.g., LangChain, LlamaIndex, CrewAI), Familiarity with vector databases
Experience with cloud platforms (AWS, Azure AI, Google Cloud Vertex AI) and containerization technologies
Proven ownership of complex, cross-cutting agentic systems spanning multiple teams or products.
Strong engineering fundamentals across backend systems, APIs, data pipelines, and cloud infrastructure.
Deep experience across the agentic AI stack, including planning, tool use, memory, and evaluation.
Fluency with AI-assisted and agentic development workflows.
Ability to influence technical direction and align teams without formal authority.
Problem-solving, cross-functional collaboration, and the ability to articulate complex AI concepts to non-technical business stakeholders