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Python Jobs in Newnan, GA (NOW HIRING)

Superprof

Python Private Tutoring Jobs

Carrollton, GA · On-site

$45.25 - $62.50/hr

We are looking for students, professionals, retirees or anyone with a passion to share, to join the largest community of teachers worldwide! If you have free time and want to share your knowledge, we ...

Sirius XM Radio

Staff Python Engineer

Atlanta, GA · On-site

We are looking for a Staff Python Engineer to provide technical leadership across both: * Trafficking Systems - the real-time backbone that powers ad delivery and pacing across platforms. * Billing ...

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How much do python jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for python in Newnan, GA is $52.91, according to ZipRecruiter salary data. Most workers in this role earn between $43.61 and $60.10 per hour, depending on experience, location, and employer.

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

Python developers often encounter challenges such as managing dependencies, ensuring code scalability, and maintaining performance on large-scale projects. Collaboration with cross-functional teams can add complexity, especially when integrating with systems written in other languages. Adopting best practices like modular code structure, thorough documentation, and automated testing can help mitigate these challenges and streamline teamwork.

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, automationEnterprise applications, Android development, backend systems
Industry UsageTech startups, data analysis firms, automation companiesFinancial services, large enterprise software, mobile app companies

Python developers focus on scripting, data analysis, and web development, often working in startups or data-driven fields. Java developers typically work on large-scale enterprise applications and Android apps. While both roles require programming skills and similar educational backgrounds, their industry applications and project types differ significantly.

What is a Python developer?

A Python developer is a software programmer who specializes in writing, testing, and maintaining code using the Python programming language. They can work on a variety of projects, including web development, data analysis, machine learning, automation, and scripting. Python developers often collaborate with other team members to design solutions and ensure the functionality and performance of applications. Their responsibilities may also include debugging programs, integrating third-party services, and writing documentation.

What are the key skills and qualifications needed to thrive as a Python developer?

To thrive as a Python Developer, you need strong programming skills in Python, knowledge of software development principles, and typically a degree in computer science or related fields. Familiarity with frameworks like Django or Flask, version control systems such as Git, and experience with databases are highly valued, along with certifications like PCEP or PCAP. Effective problem-solving, communication, and teamwork are essential soft skills to excel in collaborative and dynamic environments. These skills collectively ensure the delivery of robust, maintainable code and efficient project outcomes in technology-driven organizations.

What is Python?

Python is a programming language used to write or develop a variety of programs and applications. The software developer community uses Python for programming because it is a simple language that is easy to test and debug. Large internet companies such as Facebook, Google, Reddit, and Amazon use Python, and so do government agencies such as NASA. Programmer professionals have used Python to help build popular software such as Autodesk Maya and other visual design applications. Financial professionals and stock traders use Python when scripting algorithms for economic predictions or computerized trading.

More about Python jobs
What are the most commonly searched types of Python jobs in Newnan, GA? The most popular types of Python jobs in Newnan, GA are:
What job categories do people searching Python jobs in Newnan, GA look for? The top searched job categories for Python jobs in Newnan, GA are:
What cities near Newnan, GA are hiring for Python jobs? Cities near Newnan, GA with the most Python job openings:
Python jobs near you
Infographic showing various Python job openings in Newnan, GA as of August 2026, with employment types broken down into 2% Internship, 90% Full Time, 2% Part Time, and 6% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $110,047 per year, or $52.9 per hour.

Senior Software Engineer - Agentic AI - Python Expert

Socket.dev

Atlanta, GA • On-site

$180 - $240/hr

Other

Posted 7 days ago

Job description

We are hiring senior engineers who build fast, think AI-first, and can take agentic AI from prototype to production. You will design, ship, and operate agentic systems that combine large language models (LLMs), tools/functions, planning, memory, evaluation, and multi-agent communication. You will work primarily in Python for AI services and integrate with our enterprise stack (TypeScript/Angular, .NET/C#, SQL Server, Azure), delivering trustworthy, cost-efficient, low-latency experiences in real customer workflows.

What You'll Do!
  • Build agentic AI applications on Azure AI Foundry: Azure OpenAI models, Prompt Flow, tools/function-calling, evaluations, vector search (Azure AI/Cognitive Search), and orchestration for multi-step reasoning and tool use.
  • Design memory & grounding: implement episodic/semantic/long-term memory with vector/graph stores; architect RAG pipelines and retrieval strategies that improve factuality and reduce latency/cost.
  • Integrate via Model Context Protocol (MCP) to standardize tool/skill access; design agent-to-agent communication, delegation, and event-driven workflows.
  • Connect agents to Microsoft Fabric (OneLake, Lakehouse, Warehouse, Real-Time Analytics) and Dataverse entities/workflows; ensure lineage, governance, and auditability.
  • Develop AI-native backend services in Python (FastAPI, asyncio) with evaluation harnesses, observability, and cost/latency/quality dashboards.
  • Embed AI features into the Speria stack: TypeScript/Angular UIs, .NET/C# services, SQL Server, NServiceBus, Azure DevOps pipelines, and Ionic/Cypress where applicable.
  • Use AI-augmented development tools like GitHub Copilot, Bolt, Cursor, Replit, and vibe-coding workflows to accelerate delivery, test generation, refactoring, and documentation.
  • Implement safety & reliability: guardrails, red-teaming, PII protection, prompt hardening, regression tests, automated evaluations; uphold SLO/SLA excellence in production.
  • Implement full cycle agentic engineering: design → model/tool selection → API & UI → deployment → monitoring → continuous improvement.
What You Bring! Core AI & Agentic Expertise
  • Proven experience building LLM-powered applications with Azure OpenAI, embeddings, vector stores, RAG, prompt engineering, and evaluation pipelines.
  • Hands-on with agent frameworks such as Semantic Kernel, LangGraph, LangChain Agents, AutoGen, or CrewAI.
  • Ability to design deterministic, evaluatable, and safe agent behaviors including function schemas, tool success metrics, fallback strategies.
  • Practical use of Prompt Flow for authoring, testing, and deploying multi-step AI workflows in Azure AI Foundry.
MCP, Memory & Agentic Communication
  • Experience building and consuming MCP services to standardize tool access across agents.
  • Implemented memory architectures (episodic, semantic, vector, graph) and long-running conversational context.
  • Designed agent-to-agent communication patterns (messaging, orchestration, delegation, arbitration).
Microsoft Data & App Platform
  • Integration with Microsoft Fabric, SQL Server, Supabase, Databricks (OneLake/Lakehouse/Warehouse/Real-Time) for grounding data, retrieval, and telemetry.
  • Working knowledge of Dataverse entities, actions, and triggers; connecting agents to line-of-business records and Power Platform workflows.
  • Databricks for ELT, Delta Lake pipelines, feature engineering, ML training/serving, MLflow tracking and model lifecycle.
  • Azure IoT Hub/IoT Edge pipelines to incorporate device telemetry and edge-to-cloud intelligence into agentic workflows.
  • Azure services: App Service/Functions/AKS, Key Vault, Storage, Event Hubs/Service Bus, Monitor/Application Insights.
Python & Backend Engineering
  • Production-grade Python (FastAPI, asyncio, type hints), Postgres/SQL, Redis, queues, OpenTelemetry, CI/CD, and containerization.
  • Strong API design, testing (unit/integration/property-based), performance tuning, and reliability engineering.
Front-End & Speria Enterprise Stack
  • Experience in TypeScript/Angular for operator consoles and human-in-the-loop oversight.
  • Ability to integrate with .NET/C#, SQL Server, NServiceBus and Azure DevOps in our enterprise environment.
AI-Native Dev Workflow & Culture
  • Daily use of GitHub Copilot, Bolt, Cursor, Replit, and vibe-coding to speed delivery and raise quality.
  • Mentor teams in prompting, agent behavior design, context management, evaluation, and AI-assisted engineering practices.
  • Seasoned aptitude for action, tight feedback loops, crisp written communication, and ownership mindset.
Success Looks Like (Outcomes)
  • Quality & reliability: rising agent tool-use success rate; falling hallucination/retry rates; low incident volume; fast MTTR.
  • Performance & cost: P50/P95 latency and token-cost budgets met; measurable efficiency gains across services.
  • Adoption & impact: shipped features used by real users; clear business KPIs improved via automation/intelligence.
  • Engineering excellence: high test coverage, stable CI/CD, observable systems, and healthy on-call posture.
Tooling & Stack Summary
  • AI & Agentic: Azure AI Foundry (Azure OpenAI, Prompt Flow, evaluations), MCP, Semantic Kernel, LangGraph, LangChain, AutoGen, CrewAI, HuggingFace embeddings, vector DBs, Azure AI/Cognitive Search, RAG, memory architectures.
  • Data & Integration: Databricks (ELT, ML, Delta Lake, MLflow), Microsoft Fabric (OneLake/Lakehouse/Warehouse/Real-Time), Dataverse, Event Hubs/Service Bus.
  • IoT: Azure IoT Hub, IoT Edge, stream ingestion & device telemetry flows.
  • Services: Python (FastAPI, asyncio), .NET/C#, REST/gRPC, containers, CI/CD with Azure DevOps.
  • Frontend: TypeScript/Angular, Ionic; E2E testing with Cypress.
  • AI-Native Dev Tools: GitHub Copilot, Bolt, Cursor, Replit, vibe-coding workflows.
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