Gen AI Developer

We are seeking a highly skilled Senior Generative AI Developer to join our AI/ML team. This role focuses on leveraging cutting-edge Generative AI (GenAI) technologies to drive innovation and efficiency in software development and business processes. The ideal candidate will work on advanced techniques such as Retrieval-Augmented Generation (RAG), document chunking, and data embedding across multiple vector databases. They will collaborate closely with cross-functional teams to design, implement, and optimize AI-driven solutions, with exposure to cloud-native AI platforms like Amazon Bedrock and Microsoft Azure OpenAI considered a plus.

• Develop and deploy GenAI-based applications to solve complex business problems.
• Implement RAG frameworks to enhance information retrieval and response accuracy.
• Design and optimize document chunking strategies tailored to specific data types and use cases.
• Build and manage data embeddings using various vector databases for high-performance similarity searches.
• Collaborate with data engineers and scientists to integrate AI solutions seamlessly into existing pipelines.
• Explore and implement best practices for leveraging Amazon Bedrock and Azure OpenAI services.
• Stay updated on emerging trends and technologies in the GenAI and AI/ML landscape.

Mandatory Skills:

• Proficiency in Generative AI frameworks and technologies like
  • Prompt Engineering - creating specific prompts to guide LLM outputs
  • Fine Tuning and Few-Shot learning - Adapting LLMs for domain-specific tasks.
  • Retrieval-Augmented Generation (RAG) - Combining LLMs with external data retrieval systems
  • Text-to-Text Transfer Transformation (T5) - Framework for translating tasks into text forms.
• Expertise in designing and implementing chunking strategies for diverse datasets.
• Strong knowledge of data embedding techniques and working experience with vector databases like Pinecone, Weaviate, or Milvus.
• Solid programming skills in Python, with experience in AI/ML libraries such as TensorFlow, PyTorch, or Hugging Face Transformers.
• Familiarity with cloud platforms and services for AI/ML workloads (AWS or Azure).
• Experience with API integration for AI services and building scalable applications.
• Hands-on experience with Amazon Bedrock and/or Microsoft Azure OpenAI services.
• Knowledge of natural language processing (NLP) techniques and large language model (LLM) fine-tuning.
• Exposure to different chunking strategies, including overlap and semantic segmentation.
• Understanding of DevOps practices for deploying and managing AI models in production.
• Strong problem-solving and analytical skills with a focus on delivering value-driven solutions.

Years of Experience:

• Overall experience - 5 to 7 years
• Hands-on experience in Python - 4 to 5 years
• AI/ML experience - 3 to 4 years
• GenAI experience (good to have) - 1 to 2 years