If not in Atlanta area - job can be fully remote
What You’ll Work On
Document Intelligence: Extracting and analyzing large volumes of corporate documents using NLP and AI
Conversational AI: Building enterprise chat systems for knowledge discovery and decision support
GenAI & LLMs: Developing, optimizing, and monitoring LLM and RAG pipelines
Enterprise Integration: Integrating AI solutions with corporate systems (OAuth, LDAP, cloud services)
Scalable Platforms: Designing microservices-based, production-ready AI solutions
Key Responsibilities
Enhance and maintain an enterprise AI chat and document intelligence platform
Develop and optimize RAG pipelines and LLM integrationsRAG
Build backend APIs and AI tools for scalable, multi-team use
Collaborate with business teams to translate document and data needs into AI solutions
Support production deployments with monitoring, logging, and performance optimization
Core Technologies
Languages: Python, JavaScript/TypeScript
AI/ML: LLMs (Claude, GPT), LangChain, vector search, NLP libraries
Backend: FastAPI, Node.js, Express
Cloud & DevOps: AWS (ECS, EKS, S3, Lambda, Bedrock), Docker, Kubernetes, CI/CD
Databases: MongoDB, vector databases
Required Qualifications
Bachelor’s degree in Computer Science, Data Science, ML, Linguistics, or related field
2+ years of experience in NLP, AI, or LLM-based development
Strong experience building APIs and production AI systems
Familiarity with RAG architectures, embeddings, and semantic search
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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