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Python Developer Jobs in Acworth, GA (NOW HIRING)

The Caldwell Group

Python Engineer

Atlanta, GA · On-site

· 8-10 years experience in Application Development, engineering, implementing and supporting enterprise solutions · Advanced experience in Python, Git, Bitbucket Pipelines · AWS Experience (Lambda ...

Kemper

Python Engineer Manager

Alpharetta, GA · On-site

... engineering, data analysis or a similar role Proven experience in managing technical team and mentoring. * 3+ years experience in Python development, with experience creating python-based ...

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All JobsPython Developer JobsPython Developer Jobs in Acworth, GA

Python Developer information

See Acworth, GA salary details

$11

$52

$77

How much do python developer jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for python developer in Acworth, GA is $52.33, according to ZipRecruiter salary data. Most workers in this role earn between $43.12 and $59.42 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 does a Python developer do?

A Python Developer designs, codes, and maintains software applications using the Python programming language. They often work on web applications, data analysis, automation scripts, and more. Their responsibilities can include writing and testing code, debugging programs, integrating third-party services, and collaborating with other developers and stakeholders. Python Developers are valued for their ability to create efficient, scalable, and readable code. They may also be involved in deploying applications and maintaining technical documentation.

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.

How much do Python developers get paid?

Python developers' salaries vary based on experience, location, and skill level, but they typically earn between $70,000 and $120,000 annually in the United States. Senior developers with expertise in frameworks, data analysis, or machine learning can earn higher salaries, especially in tech hubs. Entry-level positions generally start around $60,000 to $80,000.

Is Python in demand in 2026?

Python developers are expected to remain in high demand through 2026 due to the language's widespread use in data science, web development, automation, and artificial intelligence. Proficiency in frameworks like Django or Flask and knowledge of related tools can enhance job prospects in this field.

Is there a demand for Python developers?

Python developers are in high demand across various industries such as technology, finance, and data science due to Python's versatility and widespread use in web development, automation, and machine learning. Employers seek professionals with skills in frameworks like Django or Flask and knowledge of data analysis tools like Pandas and NumPy, making Python a valuable programming language for job seekers.

What jobs can a Python Developer get?

A Python Developer can work in roles such as software engineer, web developer, data analyst, data scientist, machine learning engineer, automation engineer, and backend developer. These positions often require knowledge of frameworks like Django or Flask, and familiarity with databases and version control systems.
More about Python Developer jobs

What are the most commonly searched types of Python Developer jobs in Acworth, GA?

The most popular types of Python Developer jobs in Acworth, GA are:

What job categories do people searching Python Developer jobs in Acworth, GA look for?

The top searched job categories for Python Developer jobs in Acworth, GA are:

What cities near Acworth, GA are hiring for Python Developer jobs?

Cities near Acworth, GA with the most Python Developer job openings:

Python Developer jobs near you
Infographic showing various Python Developer job openings in Acworth, GA as of August 2026, with employment types broken down into 1% Internship, 79% Full Time, 13% Part Time, 1% Temporary, and 6% Contract. Highlights an 76% Physical, 7% Hybrid, and 17% Remote job distribution, with an average salary of $108,843 per year, or $52.3 per hour.

Senior Software Engineer - Agentic AI - Python Expert

Socket.dev

Atlanta, GA • On-site

$180 - $240/hr

Other

Posted 14 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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