Python/GenAI Consultant

Python/GenAI Consultant

Posted Today by TechVirtue LLC

Negotiable
Undetermined
Remote
Remote

Summary: The Python/GenAI Consultant role involves developing and implementing Generative AI solutions using Python for various business applications. The consultant will be responsible for building proof of concepts (PoCs) and optimizing large language models (LLMs) while integrating AI solutions with existing systems. This position is remote and focuses on long-term contract work. The role requires a strong understanding of Agentic AI and related concepts to enhance model performance and task execution.

Key Responsibilities:

  • Develop and implement Generative AI solutions using Python for business use cases
  • Build and demonstrate GenAI PoCs to validate feasibility and performance
  • Work with LLMs using platforms like OpenAI and optimize prompts
  • Design and implement RAG pipelines for contextual data retrieval
  • Develop and orchestrate Agentic AI systems for multi-step task execution
  • Apply MCP concepts for managing context, tools, and model interactions
  • Integrate AI solutions with APIs, databases, and enterprise systems
  • Monitor, evaluate, and improve model performance (accuracy, latency, cost)

Key Skills:

  • Python
  • Gen AI PoC
  • LLM
  • RAG
  • MCP concept
  • Agentic AI

Salary (Rate): undetermined

City: undetermined

Country: undetermined

Working Arrangements: remote

IR35 Status: undetermined

Seniority Level: undetermined

Industry: IT

Role: Python/GenAI Consultant
Location: Remote
Duration: Long term
Contract type: W2 Contract

Skills: Python, Gen AI Poc, LLM, RAG, mcp concept, Agentic AI

Responsibilities:
Develop and implement Generative AI solutions using Python for business use cases
Build and demonstrate GenAI PoCs to validate feasibility and performance
Work with LLMs using platforms like OpenAI and optimize prompts
Design and implement RAG pipelines for contextual data retrieval
Develop and orchestrate Agentic AI systems for multi-step task execution
Apply MCP concepts for managing context, tools, and model interactions
Integrate AI solutions with APIs, databases, and enterprise systems
Monitor, evaluate, and improve model performance (accuracy, latency, cost)