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Python Developer Jobs in Sherman Oaks, CA (NOW HIRING)

CHAOS Industries

Cloud DevSecOps Engineer

Hawthorne, CA · On-site

$140K - $220K/yr

Manage and orchestrate containerized Python package applications using Docker (Swarm and/or Compose ... Contribute to the overall improvement of our DevOps practices * Work full-time on-site in our ...

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How much do python developer jobs pay per hour?

As of May 29, 2026, the average hourly pay for python developer in Sherman Oaks, CA is $61.12, according to ZipRecruiter salary data. Most workers in this role earn between $50.38 and $69.42 per hour, depending on experience, location, and employer.

What Does a Python Developer Do?

As a Python developer, your job is to use the Python programming language to develop, implement, and debug a project. In this role, you may create an application for your employer, design the framework for your code, build tools as necessary to get the job done, create websites, or publish new services. Python developers often work with data collection and analytics to create useful answers to questions and provide insight where it's needed most. Like most programming positions, the specifics of this job vary based on the needs of your employer. Some Python developers work as independent contractors instead of being exclusive to one company.

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

To thrive as a Python Developer, you need strong programming skills in Python, a solid understanding of algorithms and data structures, and often a degree in computer science or a related field. Familiarity with frameworks like Django or Flask, version control systems such as Git, and knowledge of databases and cloud services are commonly required. Problem-solving ability, attention to detail, and effective communication help developers collaborate and deliver high-quality code. These skills and qualities are vital to building efficient, scalable software solutions and contributing effectively to development teams.

What are some common challenges Python Developers face when working on large-scale projects?

Python Developers working on large-scale projects often encounter challenges such as managing codebase complexity, ensuring consistent code style among team members, and optimizing application performance. Collaboration with other developers becomes essential, often requiring the use of version control systems and code review processes. Additionally, integrating Python code with other technologies or legacy systems can present unique compatibility and testing hurdles. Proactively adopting best practices like modular architecture and thorough documentation can help mitigate these issues.

What is the difference between Python Developer vs Java Developer?

AspectPython DeveloperJava Developer
Required CredentialsBachelor's in CS or related field, Python certifications (optional)Bachelor's in CS or related field, Java certifications (optional)
Work EnvironmentWeb development, data science, automation, scriptingEnterprise applications, Android development, backend systems
Industry UsageTech startups, data companies, automation firmsFinancial services, enterprise software, mobile app companies
Common Search/ComparisonOften compared for backend and scripting rolesCompared for enterprise and mobile app development

Python Developers and Java Developers share similar educational backgrounds and often work in backend environments. However, Python is favored for data science, scripting, and rapid development, while Java is preferred for large-scale enterprise applications and Android development. Both roles are highly sought after, but their industry focus and project types differ.

More about Python Developer jobs
What cities near Sherman Oaks, CA are hiring for Python Developer jobs? Cities near Sherman Oaks, CA with the most Python Developer job openings:
Python Developer jobs near you

Agentic AI Developer

Purple Drive Technologies

Woodland Hills, CA • On-site

Full-time

Posted 11 days ago

Job description

Overview:
Description:
Agentic AI systems preferably AWS Bedrock LLM, Python, AI agent frameworks such as LangGraph, LlamaIndex, LangChain, or AutoGen
"Design, develop, and deploy agentic AI systems preferably AWS Bedrock LLM that enhance decision-making and automate workflows across various applications. Work at the intersection of backend engineering, applied machine learning, and agent orchestration, collaborating with cross-functional teams to translate business needs into robust, scalable, and ethical AI solutions.
Key Responsibilities
• Agent Development: Design and implement intelligent agents capable of autonomous decision-making, task orchestration, and interaction with external APIs, tools, and databases.
• System Architecture: Architect and scale backend services, APIs, and microservices that support ML-driven and agentic AI applications. This includes designing infrastructure for agent tool use, memory, and planning.
• LLM Integration: Integrate large language models into complex enterprise workflows, CI/CD pipelines, and other business processes.
• Agent Orchestration: Build and prototype agentic workflows using advanced orchestration techniques and frameworks (e.g., LangGraph, CrewAI, AutoGen).
• Evaluation and Optimization: Build robust evaluation frameworks to measure agent performance, accuracy, and reliability, and continuously improve agent logic through prompt engineering and other optimization techniques.
• Collaboration: Partner with product managers, data scientists, DevOps engineers, and business stakeholders to gather requirements and drive the adoption of agentic AI solutions.
• AI Governance and Ethics: Ensure all solutions are aligned with enterprise security protocols, data governance policies, and ethical AI principles.
• Research and Innovation: Stay current with emerging trends and research in agentic AI and related technologies to inform strategic technical decisions.
Required Skills and Qualifications
• Experience:
o 7+ years of experience in AI/ML development, with a specific focus on agentic systems, autonomous workflows, or LLM-based applications.
o Proven experience building production-level AI or ML systems.
• Technical Skills:
o Programming: Strong proficiency in Python is essential, with experience in backend frameworks like FastAPI or Flask.
o AI Frameworks: Hands-on experience with AI agent frameworks such as LangGraph, LlamaIndex, LangChain, or AutoGen.
o Data and Storage: Expertise with vector databases (e.g., Pinecone, Weaviate, PGVector) and general databases (SQL and NoSQL).
o Cloud Platforms: Experience with cloud environments (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
o MLOps: Familiarity with MLOps principles and tools for deploying, monitoring, and managing AI agents in production.
• Agentic Concepts:
o Deep understanding of LLMs and agentic AI concepts, including autonomous planning, reasoning chains, memory management, and tool use.
o Experience with advanced prompt engineering and orchestration logic."
"o Programming: Strong proficiency in Python is essential, with experience in backend frameworks like FastAPI or Flask.
o AI Frameworks: Hands-on experience with AI agent frameworks such as LangGraph, LlamaIndex, LangChain, or AutoGen.
o Data and Storage: Expertise with vector databases (e.g., Pinecone, Weaviate, PGVector) and general databases (SQL and NoSQL).
o Cloud Platforms: Experience with cloud environments (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
o MLOps: Familiarity with MLOps principles and tools for deploying, monitoring, and managing AI agents in production."

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