| Summary The Generative AI Scientist designs, develops, and supports enterprise-grade AI solutions focused on document intelligence, conversational AI, and large language model (LLM) applications. This role works on scalable, production-ready platforms that extract insight from large volumes of corporate data, enable knowledge discovery, and support decision-making across the enterprise.
The ideal candidate has hands-on experience with NLP, LLMs, and Retrieval-Augmented Generation (RAG) pipelines, strong backend development skills, and experience deploying AI systems in cloud environments. Responsbilities - Enhance and maintain an enterprise AI chat and document intelligence platform
- Design, develop, and optimize LLM and RAG pipelines, including embeddings and semantic search
- Build backend APIs and AI services for scalable, multi-team usage
- Develop conversational AI systems for enterprise knowledge discovery and decision support
- Integrate AI solutions with enterprise systems, including OAuth, LDAP, and cloud services
- Translate business and document requirements into effective AI solutions
- Support production deployments through monitoring, logging, troubleshooting, and performance optimization
- Contribute to scalable, microservices-based AI platforms
Core Technologies and Tools - Programming Languages: Python, JavaScript, TypeScript
- AI / Machine Learning: LLMs (Claude, GPT), LangChain, vector search, embeddings, NLP libraries
- Backend Development: FastAPI, Node.js, Express
- Cloud & DevOps: AWS (ECS, EKS, S3, Lambda, Bedrock), Docker, Kubernetes, CI/CD pipelines
- Databases & Storage: MongoDB, vector databases
Required Qualifications - Bachelor's degree in Computer Science, Data Science, Machine Learning, Linguistics, or a related field
- 2+ years of experience in NLP, AI, or LLM-based application development
- Strong experience building and maintaining production-ready APIs and AI systems
- Familiarity with RAG architectures, embeddings, semantic search, and vector databases
- Experience deploying AI solutions in cloud environments
Preferred Qualifications - Master's or PhD in a related field
- Experience with MLOps, microservices, and enterprise authentication systems
- Knowledge of advanced NLP techniques and observability tooling
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