Haystack
← Back to Jobs
Technology
IN

AI/ML Engineer

IntraedgePhoenix, AZ🇺🇸United StatesPosted 20 Aug 2026

Why This Role Stands Out

This on-site hybrid role offers a fantastic opportunity to design and build cutting-edge AI/ML and generative AI solutions, leveraging your expertise in Python, LLMs, and RAG. You'll thrive here if you're a mid-senior engineer with a passion for innovation, collaboration, and driving impactful advancements in AI technology. Apply now to shape the future of AI with Intraedge!

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Phoenix, AZ, United States
Posted
1 week ago
DockerSQLAWSMLOpsMLflowNLPScikit-learnApacheAzureGenerative AIGitGoogle CloudKafkaPhoenixPyTorchPythonRESTTensorFlow

Job Description

Job Title: : AI/ML Engineer
Location: Phoenix, AZ (Day 1 onsite – Hybrid 3 days a week in office)
Duration: Long Term Contract


Responsibilities
Design, build, and enhance AI/ML and generative AI solutions using Python, large language models (LLMs), retrieval-augmented generation (RAG), prompt engineering, and agentic AI frameworks.
Partner with Security, Risk, Engineering, Governance, and Data teams to deliver secure, reliable, scalable, and responsible AI solutions.
Develop and support data-processing, model-deployment, and monitoring workflows.
Drive continuous improvements in code quality, system performance, scalability, maintainability, and operational reliability.
Minimum Qualifications
6+ years of hands-on professional experience in Python development.
Experience with one or more machine-learning frameworks, such as PyTorch, TensorFlow, or scikit-learn.
Practical knowledge of LLMs, natural language processing (NLP), embeddings, RAG, prompt engineering, and AI application development.
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 REST APIs, Git-based development workflows, and core cloud concepts across AWS, Google Cloud, or Microsoft Azure.
Familiarity with containerization technologies, such as Docker, and CI/CD practices.
Exposure to MLOps, workflow orchestration, and data-processing technologies, such as MLflow, Kubeflow, Argo Workflows, Kafka, Spark, or Apache NiFi.

Similar jobs