Python with AI Developer

We are looking for an expert-level Python developer with deep expertise in Large Language Models (LLMs) and AI/ML frameworks. The ideal candidate will be skilled in building high-performance applications, fine-tuning AI models, and leveraging modern Python (3.9+) features including async/await for concurrent API integrations. Experience with AWS Bedrock and vector database technologies is essential, with MLOps capabilities considered a strong plus.

Key Responsibilities

• Design, develop, and deploy Python-based applications using Python 3.9+ features such as async/await for concurrent API calls.
  
• Fine-tune and optimize AI models using PyTorch and TensorFlow.
  
• Build and integrate applications using LLM libraries and frameworks like FastAPI and LangChain.
  
• Implement RAG (Retrieval-Augmented Generation) pipelines and manage vector embeddings for efficient knowledge retrieval.
  
• Work with DynamoDB and vector database solutions for AI-driven search and data processing.
  
• Develop and manage prompt engineering for LLM-based solutions.
  
• Integrate and utilize AWS Bedrock for deploying and managing LLM applications.
  
• Collaborate using GIT workflows and contribute to CI/CD pipelines for continuous delivery.
  

Required Skills

• Python (must-have):

  Expert-level coding, concurrency (async/await), API integration.

• AI/ML (must-have):

  LLM's, RAG implementation, vector embeddings.

• Frameworks:

  FastAPI, LangChain.

• Model Development:

  PyTorch, TensorFlow fine-tuning.

• Databases:

  DynamoDB, vector databases.

• Cloud Services:

  Understanding of AWS Bedrock.

• Version Control & DevOps:

  GIT, CI/CD pipeline knowledge.

Good to Have

• MLOps experience for ML lifecycle automation and deployment.
  
• Prior experience with large-scale production AI systems.
  

Qualifications

• Bachelors or Master’s degree in Computer Science, AI/ML, or related field.
  
• 5+ years of professional experience in Python development and AI/ML systems.
  
• Proven track record of deploying LLM-based applications.