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# Senior AI Engineer at Phoenix, AZ

- **Company:** Apptad Inc.
- **Location:** Phoenix, AZ, United States
- **Experience:** Expert
- **Salary:** $197,600.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software as a Service, Cloud Computing, Distributed Systems, Python (Programming Language), Machine Learning, Node.Js, Open Source Technology, Software Safety, Software Engineering, TypeScript, Pytorch, Large Language Models, Multi-Agent Systems, Backend, Event Driven Architecture, Build Management, Kubernetes, HuggingFace, Apache Kafka, Machine Learning Operations, Virtual Agents, Software Coding, Automation Anywhere, Microservices
- **Published:** June 5, 2026
- **Apply:** https://www.careerjet.com/jobad/usa00d9ac80236af0f83665a56a167fd11

## About the Role

We are looking for a Senior AI Engineer specializing in Agentic AI to design and build intelligent systems that can reason, plan, and take actions autonomously. This is a hands-on, individual contributor role where you will lead technical decisions and develop scalable AI solutions used across multiple products., * 10+ years of experience in backend or distributed systems engineering

 * Strong coding skills (Python / TypeScript / Go)
 * Experience with cloud platforms (AWS or GCP) and Kubernetes
 * Hands-on experience with LLMs, AI agents, or ML systems
 * Knowledge of tools like LangChain, LangGraph, LlamaIndex, or similar
 * Experience with APIs, microservices, and event-driven systems (Kafka, etc.)
 * Strong problem-solving skills and ability to work in ambiguous environments, * Experience building AI systems in fintech or regulated industries
 * Familiarity with RAG pipelines, evaluation frameworks, and AI safety
 * Experience with Hugging Face, PyTorch, or ML model deployment
 * Contributions to AI/ML or open-source projects

## Description

* Design and build AI agent systems that can plan, make decisions, and interact with tools/APIs
 * Develop and maintain production-grade AI workflows using LLMs and agent frameworks
 * Work on core components like:

 * Agent orchestration
 * Memory and planning systems
 * RAG (retrieval-based AI pipelines)
 * LLM integration and APIs
 * Lead technical design discussions and guide engineering teams
 * Ensure AI systems are reliable, scalable, and safe for enterprise use
 * Collaborate with product and UX teams to improve AI-driven user experiences
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