Manager, Data & AI Enablement - Sales & Service

Qualifications

• 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

• Programming Languages: Python, JavaScript, TypeScript

• Cloud & DevOps: AWS (ECS, EKS, S3, Lambda, Bedrock), Docker, Kubernetes, CI/CD pipelines

• 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

• 5 more items(s)

Responsibilities

• 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

• 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

• AI / Machine Learning: LLMs (Claude, GPT), LangChain, vector search, embeddings, NLP libraries

• Backend Development: FastAPI, Node.js, Express

• Databases & Storage: MongoDB, vector databases

• 10 more items(s)

More job highlights

Job description

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 idea...l 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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