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Python Ai Jobs in Pennsylvania (NOW HIRING)

Sarian, Inc.

Agentic AI Developer

PA · On-site

Python, LangChain, LangGraph, Azure AI Foundry Roles & Responsibilities: * Agentic System Design: Architect, build, and optimize AI agents using multi-agent frameworks (e.g., LangGraph, AutoGen ...

Moder

Forward Deployed AI Engineer

Conshohocken, PA · On-site

$120 - $180/hr

The Forward Deployed AI Engineer is responsible for designing, developing, and deploying data and ... Strong proficiency in SQL and Python and/or PySpark.Knowledge of data engineering, ETL development ...

eTeam

AI Engineer

Malvern, PA · On-site

The role involves utilizing Python, AWS, and Node.js to develop and implement AI solutions. Qualifications : Required : • Experience in Python • Experience in Amazon Web Service (AWS) • ...

YO AI Labs

AI Engineer - Remote

Philadelphia, PA · Remote

$80 - $120/hr

No prior AI experience is required. Key Responsibilities * Create reinforcement learning ... Strong proficiency in Python 3, Java, Rust, C++, or TypeScript . * Strong understanding of ...

YO AI Labs

AI/ML Engineer - Remote

Philadelphia, PA · Remote

$200 - $350/hr

Strong Python proficiency for AI/ML development, including REST APIs and SDK integrations. * Hands-on production experience with LLMs, RAG, and prompt engineering . * Experience with multi-agent ...

YO AI Labs

AI Trainer - Remote

Philadelphia, PA · Remote

$80 - $120/hr

No prior AI experience is required. Key Responsibilities * Create reinforcement learning ... Strong proficiency in Python 3, Java, Rust, C++, or TypeScript . * Strong understanding of ...

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Python Ai information

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How much do python ai jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for python ai in Pennsylvania is $58.76, according to ZipRecruiter salary data. Most workers in this role earn between $48.41 and $66.73 per hour, depending on experience, location, and employer.

What is a Python AI?

A Python AI job involves developing, implementing, and optimizing artificial intelligence models using Python. Professionals in this role work with machine learning frameworks like TensorFlow, PyTorch, and scikit-learn to build automation, predictive analytics, and AI-driven solutions. Responsibilities may include data preprocessing, model training, fine-tuning algorithms, and deploying AI models into production. These roles are common in industries like healthcare, finance, and tech, where AI is used for tasks such as natural language processing, computer vision, and recommendation systems.

What does a Python AI do?

As a Python AI professional, your day-to-day responsibilities usually involve designing, developing, and testing machine learning models, cleaning and analyzing data, and implementing data pipelines. You’ll likely collaborate closely with data scientists, software engineers, and product managers to integrate AI solutions into real-world applications. Regular tasks also include code review, documentation, and participating in team meetings to review progress and brainstorm solutions to technical challenges. These activities not only foster collaboration but also ensure high-quality, scalable AI products.

What skills and qualifications are needed for a Python AI?

To thrive as a Python AI professional, you need strong programming skills in Python, a solid understanding of machine learning algorithms, data structures, and often a degree in computer science or a related field. Proficiency with libraries like TensorFlow, PyTorch, scikit-learn, and experience using version control systems such as Git are typically required, while certifications in AI or data science can be advantageous. Analytical thinking, problem-solving abilities, and effective communication skills help you interpret results and collaborate with multidisciplinary teams. These competencies enable the development, deployment, and optimization of AI-driven solutions in a fast-evolving technical landscape.

Can you do AI with Python?

Python AI refers to roles involving the development and implementation of artificial intelligence using Python programming. These jobs typically require knowledge of machine learning libraries like TensorFlow or PyTorch, data analysis skills, and experience with algorithms. Python's simplicity and extensive ecosystem make it a popular choice for AI development in various industries.

What are the most commonly searched types of Python Ai jobs in Pennsylvania?

The most popular types of Python Ai jobs in Pennsylvania are:

What are popular job titles related to Python Ai jobs in Pennsylvania?

For Python Ai jobs in Pennsylvania, the most frequently searched job titles are:

What job categories do people searching Python Ai jobs in Pennsylvania look for?

The top searched job categories for Python Ai jobs in Pennsylvania are:

Python Ai jobs near you
Infographic showing various Python Ai job openings in Pennsylvania as of August 2026, with employment types broken down into 75% Full Time, 20% Part Time, 4% Contract, and 1% Nights. Highlights an 65% Physical, 5% Hybrid, and 30% Remote job distribution, with an average salary of $122,225 per year, or $58.8 per hour.

Agentic AI Developer

Sarian, Inc.

PA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Skill: Agentic AI Developer
  • The Agentic AI Developer will design, build, and operationalize governed AI agent systems that autonomously plan, reason, and execute complex workflows across enterprise data and risk platforms.
  • This role focuses on developing multi agent, event driven AI solutions using Python, LangChain, LangGraph, and Azure AI Foundry, with strong emphasis on explainability, human in the loop control, and regulatory readiness.

Primary Skills:
  • Python, LangChain, LangGraph, Azure AI Foundry

Roles & Responsibilities:
  • Agentic System Design: Architect, build, and optimize AI agents using multi-agent frameworks (e.g., LangGraph, AutoGen, CrewAI).
  • Reasoning & Planning: Implement advanced prompting strategies, such as chain-of-thought, reflection, and self-correction loops to enhance agent decision-making.
  • Tool Integration: Connect AI agents to APIs, databases, and third-party SaaS platforms to enable autonomous action-taking.
  • Memory & Context: Design short-term and long-term memory systems .
  • (RAG, vector databases) so agents can maintain state and context over long-running workflows.
  • Production Deployment: Transition prototypes from research to production-ready systems, ensuring low latency, high accuracy, and observability (e.g., using Amazon CloudWatch, LangSmith).
  • Safety & Governance: Implement AI guardrails, human-in-the-loop approval steps, and audit trails to ensure ethical and secure operation.

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