GenAI Developer: Python + LLMs, RAG & AI Agents

Tanisha Systems Inc; City of Albany (NY); On-site; USD 140,000 - 190,000; Full time

Job summary

Tanisha Systems Inc. seeks a highly skilled GenAI Developer with strong Python expertise to design, develop, and deploy Generative AI solutions. The role focuses on building AI-powered applications using LLMs, RAG, and agentic AI frameworks, with production-ready deployment and governance considerations.

You will design scalable AI systems, integrate LLMs with enterprise workflows, and optimize AI processes for performance and cost. Collaboration with stakeholders is essential.

Qualifications

• Proficient Python programming.
• Hands-on Generative AI and LLMs experience.
• Experience with LangChain and LangGraph.
• Knowledge of RAG, embeddings, and semantic search.
• REST API development using FastAPI or Flask.

Responsibilities

• Design, develop, and deploy Generative AI applications with Python.
• Build AI-powered chatbots, copilots, and document-processing solutions.
• Develop and implement RAG architectures using vector databases.
• Integrate and fine-tune LLMs (GPT, Claude, Llama, Gemini, Mistral).
• Create AI agents using LangChain, LangGraph, CrewAI, or AutoGen.
• Develop REST APIs and microservices with FastAPI/Flask.
• Implement prompt engineering to optimize accuracy and performance.
• Work with structured and unstructured data (PDFs, emails, documents).
• Integrate AI with enterprise apps, databases, and third-party systems.
• Monitor model performance, latency, and cost; ensure governance and compliance.
• Collaborate with stakeholders to deliver AI solutions.

Skills

Python

Generative AI

LLMs

LangChain

LangGraph

RAG

embeddings

semantic search

prompt engineering

FastAPI

Flask

Tools

FastAPI

Flask

Job description

Tanisha Systems Inc. seeks a highly skilled GenAI Developer with strong Python expertise to design, develop, and deploy Generative AI solutions. The role focuses on building AI-powered applications using LLMs, RAG, and agentic AI frameworks, with production-ready deployment and governance considerations.

You will design scalable AI systems, integrate LLMs with enterprise workflows, and optimize AI processes for performance and cost. Collaboration with stakeholders is essential.