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Python Developer (GenAI/LLM Focus)
Ref No.: 26-00377
Location: Minneapolis, Minnesota
Position Type:Contract
Job Title: Python Developer (GenAI/LLM Focus)
Location: Minneapolis, MN (Onsite)
Duration: Contract
Job Description:
  • We are seeking a hands-on AI Full Stack Developer to build and deliver end-to-end AI-powered applications that integrate LLM/GenAI capabilities into real-world business workflows.
  • This role is focused on AI-driven product development, combining backend services, frontend experiences, APIs, and intelligent workflows to create scalable and user-centric applications (e.g., chatbots, copilots, AI assistants).
Key Responsibilities:
  • Build and deploy end-to-end AI applications (e.g., chatbot/copilot platforms) with UI, APIs, and backend services
  • Design and develop REST APIs and services for LLM inference, prompt orchestration, and agent workflows
  • Implement AI-driven user experiences, including:
  • Explainability features
  • Feedback loops
  • Human-in-the-loop (HITL) workflows
  • Develop and manage prompt flows, tool/function calling, and agent orchestration
  • Integrate AI/ML services with enterprise systems and external APIs
  • Build React (or similar) based frontends to enable intuitive interaction with AI systems
  • Ensure secure SDLC practices including code reviews, testing, dependency management, and vulnerability fixes
  • Collaborate with architecture, platform, and product teams to align with enterprise standards
  • Leverage AI coding tools (e.g., Copilot, agentic IDEs) to improve developer productivity
Required Skills (Must-Have):
  • 5+ years of full-stack software development experience
  • Strong programming skills in Python (preferred) / Java / .NET
  • Hands-on experience building LLM/GenAI-powered applications (production or strong POCs)
  • Strong experience with:
  • REST API development
  • Backend service design and integration
  • Modern frontend frameworks (React preferred)
  • Practical experience with:
  • Lang Chain / Lang Graph / agent frameworks
  • Prompt engineering and prompt workflows
  • Tool/function calling and API orchestration
  • Strong understanding of:
  • AI system design and application architecture
  • LLM integration patterns (RAG, agents, copilots)
  • Experience with CI/CD, Git workflows, and automated testing
Nice-to-Have (Highly Preferred):
  • Experience building AI copilots, chatbots, or internal AI assistants
  • Knowledge of AI observability and evaluation:
  • Prompt/version tracking
  • Model evaluation metrics
  • Experience designing AI interaction UX (explain ability, feedback, HITL)
  • Exposure to LLM runtimes, embeddings, and vector databases