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Github Copilot Jobs in Georgia (NOW HIRING)

Expert in C#, Typescript, >NET, AZURE, and demonstrated experience using GitHub Copilot Join Speria -- Build Technology That Feeds the World We're tackling one of humanity's biggest challenges ...

Experience with AI-assisted development tooling, including GitHub Copilot, Copilot CLI, Codex, or Claude Code * Experience with GitHub Actions for CI/CD, workflow automation, or pipeline ...

The team embraces AI-assisted software development tools such as GitHub Copilot and other emerging technologies to improve productivity, code quality, and engineering excellence. QUALIFICATIONS * 10+ ...

... GitHub Copilot, ChatGPT, etc.) • Strong problem-solving and communication skills • Open to contract or full-time roles Preferred : • Exposure to cloud platforms (AWS, Azure, or GCP) Company

Experience with tools such as Codex, GitHub Copilot, Claude Code , or similar AI coding agents. * Experience with large-scale software projects or architectural refactoring. * Strong technical ...

Expert in C#, Typescript, >NET, AZURE, and demonstrated experience using GitHub Copilot Join Speria -- Build Technology That Feeds the World We're tackling one of humanity's biggest challenges ...

Proactive use of AI tools (GitHub Copilot, Cursor, etc.) to accelerate technical tasks and explore new libraries. * A desire to work at the intersection of data engineering and full-stack development ...

Proactive use of AI tools (GitHub Copilot, Cursor, etc.) to accelerate technical tasks and explore new libraries. * A desire to work at the intersection of data engineering and full-stack development ...

Showing results 41-60

Github Copilot information

See Georgia salary details

$27.4K

$69K

$106.4K

How much do github copilot jobs pay per year?

As of Sep 8, 2026, the average yearly pay for github copilot in Georgia is $69,029.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,900.00 and $86,100.00 per year, depending on experience, location, and employer.

What is the difference between Github Copilot vs Software Developer?

FeatureGithub CopilotSoftware Developer
Primary RoleAI-powered code completion toolDesigning, coding, testing software applications
Required SkillsProficiency in programming, understanding of AI toolsProgramming languages, problem-solving, software design
Work EnvironmentIntegrated into IDEs, used alongside developersOffice or remote, collaborative or solo coding
CertificationsNone required, but familiarity with coding standards helpsComputer Science degree or coding certifications often preferred

Github Copilot is an AI tool that assists developers by suggesting code snippets, while a Software Developer actively writes, tests, and maintains software applications. Copilot enhances productivity but does not replace the core responsibilities of a developer. Both roles often work together in the software development process.

What are popular job titles related to Github Copilot jobs in Georgia?

For Github Copilot jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Github Copilot jobs in Georgia look for?

The top searched job categories for Github Copilot jobs in Georgia are:

What cities in Georgia are hiring for Github Copilot jobs?

Cities in Georgia with the most Github Copilot job openings:

Infographic showing various Github Copilot job openings in Georgia as of August 2026, with employment types broken down into 28% Full Time, 62% Part Time, 7% Contract, and 3% Nights. Highlights an 21% Physical, 2% Hybrid, and 77% Remote job distribution, with an average salary of $69,029 per year, or $33.2 per hour.

AI Native Development lead/ Architect

Tror AI for everyone

Atlanta, GA • On-site

Contractor

Re-posted 6 days ago


Job description

Job Role: AI Native Development lead/ Architect

Job Location: Atlanta, GA (Hybrid)

Job Type: Contract

Role Summary
We are looking for an AI Native Development Architect to design and guide the build of cloud-native, data- and AI-driven applications on AWS. You will define target architectures, enable engineering teams with reusable patterns and reference implementations, and accelerate delivery using modern AI-assisted development tools.

Key Responsibilities

  • Define end-to-end architecture for AI-native products, including application, data, integration, security, and operations on AWS.
  • Lead design reviews and provide technical direction across Python and C#/.NET codebases.
  • Architect data pipelines and analytical workloads using PySpark and AWS Glue; establish standards for data quality, lineage, and observability.
  • Design and implement scalable APIs and microservices using FastAPI (and/or .NET Web APIs) with clear contracts, versioning, and performance SLAs.
  • Establish reference architectures for LLM/RAG-enabled capabilities (e.g., retrieval patterns, prompt management, evaluation, guardrails) aligned with organizational policies.
  • Partner with Security, Platform, and DevOps teams to implement secure-by-design practices (IAM, secrets, network controls, encryption, threat modeling).
  • Define CI/CD, branching, testing, and release practices; improve developer productivity with automation and paved-road templates.
  • Champion AI-assisted engineering workflows using tools such as GitHub Copilot, Cursor, and Claude AI while ensuring code quality and compliance.
  • Mentor engineers, create technical documentation, and drive adoption of best practices across teams.

Required Skills:

  • Python: strong hands-on experience building services and data workloads using Python, PySpark, AWS Glue, and FastAPI.
  • C#/.NET: ability to design and review .NET services and libraries; familiarity with modern .NET runtime and patterns.
  • AWS: strong understanding of AWS architecture fundamentals (networking, IAM, compute, storage, managed services) and designing for scale, reliability, and cost.

AI Native Development Tools

  • Proficiency using AI coding assistants to accelerate development while maintaining engineering rigor: GitHub Copilot, Cursor, Claude AI.
  • Ability to establish team guidelines for AI-assisted coding (review standards, secure prompting, IP/compliance awareness, and validation/testing).

Preferred Qualifications

  • Experience designing GenAI solutions (RAG, tool/function calling, agents) and implementing evaluation/monitoring approaches.
  • Experience with infrastructure as code (e.g., CloudFormation/CDK/Terraform) and container platforms (Docker/ECS/EKS).
  • Knowledge of MLOps patterns (model lifecycle, feature stores, experiment tracking) and data governance concepts.
  • Strong understanding of observability practices (logs/metrics/traces) and SRE-oriented reliability design.

Soft Skills & Competencies

  • Architecture leadership: can balance short-term delivery with long-term platform thinking.
  • Clear communication: can translate complex technical decisions for engineering and business stakeholders.
  • Hands-on mindset: comfortable prototyping and jumping into code to unblock teams.
  • Quality and security focus: promotes testing discipline, secure coding, and operational readiness.
  • Collaboration and mentorship: builds alignment, coaches engineers, and scales best practices across squads.