Summary

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

Your role in our mission

Essential Job Functions

• 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.

What we're looking for

• 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

What you should expect in this role

• 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.