We are seeking an AI Engineer to design, build, and deploy enterprise-grade Generative AI applications leveraging cloud-native architectures and up-to-date LLM ecosystems. The ideal candidate will have robust data engineering foundations combined with expertise in Retrieval-Augmented Generation (RAG), agentic workflows, and AI service integration.
Responsibilities
Design and develop GenAI applications using Python and enterprise LLM platforms.
Build scalable data pipelines for structured and unstructured data processing.
Implement Retrieval-Augmented Generation (RAG) systems and vector-based search solutions.
Integrate LLMs with enterprise applications through APIs and workflows.
Develop cloud-native AI services on AWS, Azure, GCP, Databricks (DBRX), or Snowflake.
Create agent-based solutions using LangChain and LangGraph.
Ensure data quality, governance, and security compliance across AI workflows.
Optimize performance, scalability, and reliability of AI solutions.
Requirements
Core Skills
Python
SQL
ETL/ELT
Data Modeling
Data Quality
Cloud-native Development
API Integration
Data Engineering
Document Processing
Workflow design
Knowledge of LLM development
RAG
Prompt Engineering
AI Coding Assistants
Advanced Skills
RAG Data Pipelines
LLM Data Integration
AI Service Integration
Scalable AI Deployments
Agent Orchestration
Tool Calling
LangGraph
LangChain
Additional Responsibilities
Experience with Hugging Face, LangChain, OpenAI, Anthropic, Gemini, or open-source LLMs.
Familiarity with knowledge graphs and semantic search.
Experience building production-grade GenAI solutions.