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Remote Fastapi Developer Jobs in Woodstock, GA (NOW HIRING)

Victory Live

Senior Software Engineer

Atlanta, GA · Remote

$125.40K - $165.30K/yr

Remote-ready, async-first. Most decisions happen in writing through Jira, Confluence, PR ... Rails, FastAPI, .NET, Postgres, DynamoDB, MSSQL Server, Docker, Terraform * Cloud Providers: AWS ...

Ticket Evolution

Senior Software Engineer

Atlanta, GA · On-site +1

$117.80K - $155.30K/yr

Remote-ready, async-first. Most decisions happen in writing through Jira, Confluence, PR ... Rails, FastAPI, .NET, Postgres, DynamoDB, MSSQL Server, Docker, Terraform * Cloud Providers: AWS ...

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Remote Fastapi Developer information

See Woodstock, GA salary details

$15

$47

$73

How much do remote fastapi developer jobs pay per hour?

As of May 30, 2026, the average hourly pay for remote fastapi developer in Woodstock, GA is $47.64, according to ZipRecruiter salary data. Most workers in this role earn between $36.39 and $58.32 per hour, depending on experience, location, and employer.

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

To excel as a Remote FastAPI Developer, you need strong proficiency in Python programming, RESTful API design, and experience with the FastAPI framework, typically supported by a relevant degree or equivalent experience. Familiarity with tools such as Docker, Git, SQL/NoSQL databases, and cloud platforms like AWS or Azure is highly valued, and certifications in cloud or backend development can be advantageous. Excellent problem-solving, self-management, and communication skills are crucial for collaborating effectively in a remote environment. These skills ensure you can deliver robust, scalable APIs while efficiently working with distributed teams.

What are some common challenges Remote FastAPI Developers face when collaborating with distributed teams?

Remote FastAPI Developers frequently work with colleagues across different time zones and communication styles, which can make real-time collaboration and code reviews more challenging. Staying aligned on project requirements, API design standards, and deployment schedules often requires proactive communication and thorough documentation. Using tools like version control, issue trackers, and asynchronous messaging helps bridge these gaps, but developers must be disciplined about keeping everyone updated and clarifying technical decisions. Building strong remote working habits and establishing clear processes with your team can greatly improve collaboration and project outcomes.

What is a Remote FastAPI Developer?

A Remote FastAPI Developer is a software engineer who specializes in building web APIs using the FastAPI framework, while working remotely from any location. FastAPI is a modern, high-performance Python web framework used to create APIs quickly and efficiently. Remote FastAPI Developers design, implement, and maintain backend services, typically collaborating with distributed teams through online communication and project management tools. Their responsibilities often include writing clean, scalable code, integrating databases, and ensuring API security and performance.
What job categories do people searching Remote Fastapi Developer jobs in Woodstock, GA look for? The top searched job categories for Remote Fastapi Developer jobs in Woodstock, GA are:
What cities near Woodstock, GA are hiring for Remote Fastapi Developer jobs? Cities near Woodstock, GA with the most Remote Fastapi Developer job openings:
Remote Fastapi Developer jobs near you
Infographic showing various Remote Fastapi Developer job openings in Woodstock, GA as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $99,098 per year, or $47.6 per hour.

Enterprise AI Engineer (GCP)

INFT Solutions Inc

Atlanta, GA • On-site, Remote

Contractor

Posted 24 days ago

Job description

Job Description: Enterprise AI Engineer (GCP)
Location: Remote / Hybrid Focus: Agentic AI, Data Intelligence, and Enterprise Scale
Role Overview
We are looking for a Principal Enterprise AI Engineer to architect and deliver high-impact AI
solutions within the Google Cloud ecosystem. This role is designed for a technical leader who
can bridge the gap between complex data landscapes and autonomous AI systems. You will lead
the development of Agentic AI frameworks and Data Intelligence platforms that drive
significant digital transformation for global enterprise clients.
Core Responsibilities
 Architect Agentic Systems: Design and deploy multi-agent orchestration frameworks
using Vertex AI Agent Builder, LangGraph, or CrewAI to automate complex, multi-step
business workflows.
 Master RAG Architectures: Build and optimize high-performance Retrieval-
Augmented Generation (RAG) systems, ensuring LLMs are grounded in enterprise data
across BigQuery and Databricks.
 Model Strategy & Optimization: Select and fine-tune models within the Gemini 1.5
family, balancing high-reasoning capabilities (Pro) with high-speed efficiency (Flash) for
production-grade latency.
 Legacy Transformation: Lead the strategic migration of legacy analytics logic (e.g.,
SAS environments) into modern, AI-powered cloud architectures.
 GTM Collaboration: Work closely with Go-To-Market (GTM) leadership to translate
technical AI roadmaps into measurable business value for C-suite stakeholders.
Required Skill Requirements
1. Agentic AI & Orchestration
 Framework Mastery: Expert implementation of LangChain, LangGraph, or
LlamaIndex for stateful, autonomous agent development.
 Advanced Prompting: Proficiency in Chain-of-Thought (CoT), ReAct patterns, and
system instruction optimization to ensure reliable model output.
 Function Calling: Experience building custom tools that allow LLMs to interact
securely with enterprise APIs and SQL databases.
2. Data Intelligence & Engineering
 Hybrid Data Ecosystems: Deep experience integrating Google Cloud AI services with
Databricks (Delta Lake) for unified data intelligence.
 Vector Engineering: Proficiency with Vertex AI Vector Search (formerly Matching
Engine) and embedding strategies for large-scale semantic search.
 Data Flow: Skill in building scalable pipelines using Dataflow or Spark to process
unstructured data for AI readiness.
3. LLMOps & Production Engineering
 Evaluation Frameworks: Ability to build automated "LLM-as-a-judge" evaluation
pipelines to track accuracy, faithfulness, and hallucination rates.
 Cloud Infrastructure: Mastery of the Vertex AI suite (Studio, Model Garden, Pipelines)
and Infrastructure as Code (Terraform).
 Programming: Expert-level Python (FastAPI, Pydantic) and advanced SQL.
4. Strategic Governance
 Responsible AI: Implementation of safety filters, PII redaction, and ethical AI
monitoring.
 Business Translation: Ability to convert technical metrics (latency, token costs) into
business KPIs (ROI, process efficiency).
Qualifications
 Experience: 8+ years in Software Engineering or Data Science, with at least 3+ years
focused on production-grade AI/ML.
 Education: B.S./M.S. in Computer Science, AI, or a related quantitative field.
 Certifications: Google Professional Machine Learning Engineer or Professional Cloud
Architect (preferred).
Technology Stack
 AI/ML: Vertex AI, Gemini 1.5 Pro/Flash, PyTorch.
 Data: BigQuery, Databricks, Vertex Vector Search.
 Orchestration: LangGraph, Vertex AI Agent Builder.
 DevOps: GitHub Actions, Terraform, Vertex AI Pipelines.