Python AI Developer

PRI Global

$100K — $130K *
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 6-10 years of experience in relevant roles required
  • 5+ years in Software Engineering or equivalent experience
  • 5+ years of full-stack Python development expertise
  • 3+ years developing REST APIs for AI services
  • 3+ years of knowledge in Autosys, OpenShift, and GCP environments
  • 1+ year of experience working with GenAI stack

Responsibilities

  • Develop and maintain full-stack applications using Python frameworks
  • Design and implement RESTful APIs for AI services
  • Integrate front-end solutions with back-end systems
  • Manage CI/CD processes and identity access for secure deployments
  • Utilize the GenAI stack for enhancing application capabilities
  • Conduct quality assessments using LLM-as-a-Judge methodologies

Benefits

  • Day 1 onsite collaboration
  • Opportunities for continuous learning and growth
  • Access to cutting-edge technology and tools
  • Engagement in impactful AI development projects
  • Support for enterprise-level AI governance
Full Job Description
Python AI Developer
Location: Charlotte, NC

Experience: 6 to 10 years

Day 1 onsite

5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
5+ years of Python full-stack development, including RESTful API design (FastAPI, Flask, Django), web development frameworks, and front-end integration.
3+ years of experience of REST API development for AI services
3+ years of experience of strong knowledge of Autosys, OpenShift (OCP), and GCP environments.
3+ years of experience with CI/CD tools and Identity Access Management.
1+ years of experience with GenAI stack.
Desired Qualifications:
Familiarity with Google AI Development Kit (ADK) or equivalent Microsoft AI frameworks for enterprise-grade GenAI solutions like autogen, semantic kernel
Familiarity with enterprise AI governance and responsible AI frameworks
Combine human + automated evaluation for nuanced quality checks
Use LLM-as-a-Judge for scalable assessments.
Expertise in numerical libraries such as NumPy, Pandas, and experience building data-driven applications with robust performance and scalability.
Familiarity with PostgreSQL, ETL processes, and S3 data handling.
GenAI stack
Hands-on experience with LangChain, LangGraph, and LangSmith for building agentic workflows
Experience with vector databases
Proficiency in developing React-based AI agents, strong understanding of multi-agent orchestration systems
Familiarity with Model Context Protocol (MCP), enterprise-grade agentic workflows is highly desirable

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