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Associate Ai Agent Developer Jobs in Arizona (NOW HIRING)

Run prompt-injection and jailbreak testing and LLM red-teaming, and secure MCP and AI-agent ... Hands-on experience building security into CI/CD as guardrails-as-code (Azure DevOps, GitHub ...

AI IAM Architect

Tempe, AZ · Remote

$153K - $255K/yr

The AI IAM Architect partners across AI/platform engineering, IAM, security, and enterprise ... Transition validated patterns to IAM engineering for production rollout. * Define agent identity ...

Senior Software Engineer

Phoenix, AZ · On-site

$121K - $160K/yr

... based simulation engines and AI agent workflows with global enterprise clients. Key ... Apply today with your resume Oscar Associates Limited (US) is acting as an Employment Agency in ...

New

Senior Agent AI Engineer

Phoenix, AZ · On-site

$128K - $176K/yr

Senior Agent AI Engineer A job at TSMC Arizona offers an opportunity to work at the most advanced semiconductor fab in the United States. TSMC Arizona's first fab will operate its leading-edge ...

Senior Agent AI Engineer

Phoenix, AZ · On-site

$128K - $176K/yr

Senior Agent AI Engineer A job at TSMC Arizona offers an opportunity to work at the most advanced semiconductor fab in the United States. TSMC Arizona's first fab will operate its leading-edge ...

AI/ML Engineer - Remote

Phoenix, AZ · Remote

$200 - $350/hr

You will work with LLMs, RAG, prompt engineering, multi-agent systems, and cloud AI platforms to develop production-grade machine learning applications. Key Responsibilities * Design, implement, and ...

Senior AI/ML Engineer

Phoenix, AZ · On-site +1

$98K - $135K/yr

... DevOps Engineer Expert • AWS Certified Machine Learning Engineer - Associate or AWS Certified ... agent architectures, development standards, governance patterns, and evaluation methods. • ...

Showing results 21-40

Associate Ai Agent Developer information

What is the difference between Associate Ai Agent Developer vs Machine Learning Engineer?

AspectAssociate Ai Agent DeveloperMachine Learning Engineer
Required CredentialsBachelor's in CS, AI, or related field; some certificationsBachelor's or Master's in CS, Data Science, or related; advanced certifications
Work EnvironmentTech companies, AI startups, R&D labsTech firms, AI companies, research institutions
Employer & Industry UsageDevelops AI agents, chatbots, virtual assistantsDesigns ML models, algorithms, data pipelines
Common Search & ComparisonOften compared for entry-level AI rolesMore advanced, research-focused roles

The Associate Ai Agent Developer typically focuses on building and maintaining AI agents like chatbots and virtual assistants, often at an entry to mid-level. In contrast, a Machine Learning Engineer develops complex ML models and algorithms, usually requiring more advanced skills and experience. Both roles are vital in AI development but differ in scope, complexity, and specialization.

What are the most commonly searched types of Ai Agent Developer jobs in Arizona?

The most popular types of Ai Agent Developer jobs in Arizona are:

What are popular job titles related to Associate Ai Agent Developer jobs in Arizona?

For Associate Ai Agent Developer jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Associate Ai Agent Developer jobs in Arizona look for?

The top searched job categories for Associate Ai Agent Developer jobs in Arizona are:

What cities in Arizona are hiring for Associate Ai Agent Developer jobs?

Cities in Arizona with the most Associate Ai Agent Developer job openings:

Infographic showing various Associate Ai Agent Developer job openings in Arizona as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 25% Part Time, 1% Temporary, and 1% Contract. Highlights an 96% Physical, 2% Hybrid, and 2% Remote job distribution.

C2C Job opportunity: AI/ML Engineer at Phoenix, AZ

Tech Mirrors

Phoenix, AZ • On-site

$63 - $87/hr

Other

Posted yesterday

New


Job description

Role: AI/ML Engineer

Location:Phoenix, AZ (HYBRID)

Duration: Long Term Contract

Rate: $55/hr C2C

Note: Must interview onsite for 2nd round interview

About the Role

We are seeking an experienced AI/ML Engineer to design, build, and operate AI/ML infrastructure and agentic systems. This role involves developing MCP servers and agents, integrating LLMs, and implementing RAG pipelines for production environments.

Key Responsibilities
  • Design, build and operate MCP servers and MCP agents that host, orchestrate and monitor AI/agent workloads.
  • Develop agentic AI, prompt engineering patterns, LLM integrations and developer tooling for production use.
  • Own deployment, scaling, reliability and cost-efficiency on Kubernetes/Docker and Google Cloud with automated CI/CD
  • Design and implement RAG (Retrieval Augmented Generation) pipelines and integrations with vector stores and retrieval tooling; use LangChain and Langfuse for orchestration, chaining, and observability.
Core Responsibilities
  • Implement and maintain MCP server and agent code, APIs, and SDKs for model access and agent orchestration.
  • Design agent behavior, workflows and safety guards for agentic AI systems.
  • Create, test and iterate prompt templates, evaluation harnesses and grounding/chain of thought strategies.
  • Integrate LLMs and model providers (self-hosted and cloud APIs) with unified adapters and telemetry.
  • Build developer tooling: CLI, local runner, simulators, and debugging tools for agents and prompts.
  • Containerize services (Docker), manage orchestration (Kubernetes/GKE), and optimize nodes, autoscaling and resource requests.
  • Ensure observability: logging, metrics, traces, dashboards, alerting and SLOs for model infra and agents.
  • Create runbooks, playbooks and incident response procedures; reduce MTTR and perform postmortems.
  • Design and maintain RAG workflows: document chunking, embeddings, vector indexing, retrieval strategies, re ranking and context injection.
  • Integrate and instrument Lang Chain for composable chains, agents and tooling; use Langfuse (or equivalent tracing) to capture prompts, model calls, RAG traces and evaluation telemetry.
Required Skills & Experience
  • 5+ years of Strong Software Engineering (Python/NodeJS), system design and production service experience.
  • 2+ years of Experience with LLMs, prompt engineering, and agent frameworks.
  • 2+ years of Experience Practical experience implementing RAG: embeddings, vector DBs and retrieval tuning.
  • 2+ years of Experience with LangChain patterns and with toolchain telemetry (Langfuse or similar) for prompt/model traceability.
  • 5+ years of Experience with Kubernetes, Docker, CI/CD and infrastructure as code experience.
  • 2+ years of Experience with Practical experience with Google Cloud Platform services
  • 2+ years of Experience with Observability, testing, and security best practices for distributed systems.
  • 2+ years of Experience with evaluating and mitigating retrieval/augmentation failures, hallucinations, and leakage risks in RAG systems.
  • Familiarity with vendor and open-source vector stores and embedding providers
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