GenAI Tool Engineer

Position: GenAI Tool Engineer Location: Remote Duration: 6 Months Responsibilities: • Perform RAG, Grounding, Prompt Engineering in a project: Craft and refine effective prompts to achieve optimal results in various tasks related to product development. • Excellent attention to detail and organizational skills. Strong programming skills – including in python, ML ecosystem tools, and generative AI. • Knowledge + Vector Database Development: Design, develop, and implement a robust Vector Database using LLMs and other AI technologies, focusing on capturing information from diverse sources (PDFs, design documents, regulatory requirements, etc.). • Data Extraction and Structuring: Develop and implement pipelines for extracting data from unstructured documents, including tables, text, and images, structuring the data for LLM training and usage. • LLM Fine-Tuning and Training: Fine-tune and train generative AI models on client's specific engineering data and domain knowledge to create domain-specific models. • AI Tool Development: Design and develop a user-friendly GenAI tool that integrates with the knowledge base, allowing engineers to ask questions, generate technical requirements, and perform engineering analyses. • Technical Requirements Generation: Implement functionality for automatically generating technical requirements from design documents, user stories, and system requirements using LLMs. • Documentation and Knowledge Transfer: Thoroughly document all development processes, including designs, architecture, code, and training procedures. Provide adequate knowledge transfer to client's internal teams, enabling them to maintain and expand the system. • Collaboration: Work closely with the Subject Matter Experts and engineers to implement and optimize AI-powered workflows. Required: • STEM Background: Minimum 4 year experiences with a Bachelor’s or Master’s with minimum 3 year experience in a STEM field (e.g., Computer Science, Engineering, Physics, Mathematics) with a dedicated focus on AI/ML in the last 1–2 years. • Proven experience with Google Gemini / Vertex AI (Non-negotiable). Hands-on experience with Gemini 2.5 family of generative AI models and associated technologies, including training, fine-tuning, and deployment. • Languages: Proficiency in Python, TensorFlow and other Machine Learning and Artificial Intelligence libraries for building LLM agents, tools and MCP servers. • Context Engineering: Proven experience performing context engineering and prompt tunning. • Create REST-APIs to serve AI services and Front-end development for user interface design and development. • Experience with Vector databases such as Pgvector, AlloyDB etc., graph databases, and other knowledge representation technologies. Clear understanding of Retrieval Augmented Generation (RAG), knowledge representation techniques. • Unstructured Data Handling: Demonstrated ability to work with unstructured data, including text documents, images, and other media types, and perform data cleaning, preprocessing, and transformation for AI applications (Non-negotiable). Preferred: • Experience in creating REST-APIs. • Familiarity with medical device development regulations (e.g., FDA guidelines, ISO 13485). • Experience with front-end development for user interface design and development. Software Skills Required: • Python, Java, C++, C#) for building LLM agents and tools • Software Version Control: (e.g., Git, SVN) for collaborative development. • Testing and Debugging Tools: (e.g., JUnit, pytest) for ensuring the quality of code and LLM agents. • Cloud computing platforms: Experience with cloud platforms such as AWS, Azure, or GCP is beneficial for working with large language models. • Version control systems: Git for collaboration and tracking code changes (optional). Applicant Notices & Disclaimers: For information on benefits, equal opportunity employment, and location-specific applicant notices, click here