Generative AI Product Developer/Architect - RAG/LLM

GenAI Product Developer/Architect

Role Summary

We are seeking a highly skilled and innovative AI/ML Architect to lead the design and development of cutting-edge AI/ML applications. This role will focus on architecting and building robust sophisticated Agentic AI workflows including end-to-end RAG pipelines. The ideal candidate will possess a deep understanding of AI principles, a strong background in Python programming, and hands-on experience with relevant frameworks and tools. You will be responsible for translating complex business requirements into scalable and efficient AI solutions, driving innovation and delivering significant value to our :

Architect And Design GenAI Solutions

• Design and implement end-to-end RAG pipelines for various use cases, ensuring optimal performance and accuracy.
• Develop and architect Agentic AI workflows, enabling autonomous and intelligent task execution.
• Evaluate and select appropriate Large Language Models (LLMs) and other AI technologies based on project requirements.
• Create scalable and maintainable GenAI architectures that integrate seamlessly with existing systems.
  
  

RAG Pipeline Development

• Design and implement data ingestion, indexing, and retrieval strategies for RAG systems.
• Optimize RAG pipelines for performance, accuracy, and latency.
• Implement techniques for query understanding, document ranking, and response generation.
• Work with vector databases.
  
  

Agentic AI Workflow Development

• Design and implement autonomous agents capable of performing complex tasks.
• Develop orchestration frameworks for managing multiple agents and their interactions.
• Implement tools and techniques for agent planning, execution, and monitoring.
• Work with LangGraph.
  
  

Framework And Tool Expertise

• Stay up to date with the latest advancements in GenAI frameworks and tools (e.g., LangChain, AutoGen).
• Evaluate and integrate new technologies to enhance GenAI capabilities.
• Develop and maintain reusable components and libraries for GenAI applications.
  
  

Research And Innovation

• Conduct research and experimentation to explore new GenAI techniques and applications.
• Identify opportunities for innovation and drive the adoption of best practices.
• Keep up with the latest advancements in LLM technology.
  
  

Programming

Required Skills :

• Expert proficiency in Python.
• Experience with relevant Python libraries (e.g., NumPy, Pandas, Scikit-learn).
  
  

Generative AI

• Deep understanding of Large Language Models (LLMs) and their applications.
• Hands-on experience with RAG pipeline development and optimization.
• Experience with Agentic AI workflows and orchestration.
• Familiarity with vector databases (e.g., Pinecone, Weaviate, Chroma).
  
  

Frameworks And Tools

• Expertise in LangChain and LangGraph.
• Experience with AutoGen.
• Familiarity with other relevant GenAI frameworks and tools.
  
  

AI/ML Concepts

• Strong understanding of machine learning and deep learning concepts.
• Experience with natural language processing (NLP) techniques.
• Understanding of prompt engineering.
  
  

Software Development

• Experience with software development best practices (e.g., version control, testing, deployment).
• Experience with cloud platforms (e.g., AWS, Azure, GCP).
  
  

(ref:hirist.tech)