Remote GenAI Engineer - RAG, Agents & Applications

KData AI; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

KData AI is seeking an AI Engineer to design, develop, and operate production-ready GenAI applications. The role concentrates on GenAI, RAG, and agentic workflows using foundation models, enterprise data, APIs, and cloud services.

You will work with AI Architects, software engineers, and product teams to deliver secure, observable, and cost-aware AI capabilities like conversational assistants, document intelligence, summarization, and knowledge Q&A. Remote position.

Qualifications

• Strong Python skills with modular, testable code.
• Experience building GenAI/LLM apps and integrations.
• Understanding of tokens, prompts, and model constraints.
• Experience deploying AI services via cloud and container tech.

Responsibilities

• Develop maintainable Python services for GenAI apps and data processing.
• Implement prompt templates, tool calls, and model integrations; iterate_based_on_requirements.
• Build end-to-end RAG pipelines: ingestion, embedding, retrieval, grounding.
• Integrate vector/ hybrid search and tune retrieval quality with metrics.
• Create agentic workflows with state, routing, retries, and approvals.
• Integrate enterprise APIs and data sources with proper authentication/permissions.
• Build APIs and dashboards with FastAPI/Streamlit; collaborate with frontend engineers.
• Deploy and monitor AI services in cloud using CI/CD and containerization.
• Instrument apps with logs, traces, and cost metrics; write tests.

Skills

Python

GenAI development

LLM integration

REST APIs

Testing & CI/CD

Education

Bachelor’s degree in CS/Engineering

Tools

FastAPI

Streamlit

Pydantic

FAISS

LangChain

Docker

Job description

KData AI is seeking an AI Engineer to design, develop, and operate production-ready GenAI applications. The role concentrates on GenAI, RAG, and agentic workflows using foundation models, enterprise data, APIs, and cloud services.

You will work with AI Architects, software engineers, and product teams to deliver secure, observable, and cost-aware AI capabilities like conversational assistants, document intelligence, summarization, and knowledge Q&A. Remote position.