Senior Artificial Intelligence Engineer

Base salary: $250k-$350k

Total Comp: $400k-$500k

Core Responsibilities

Data Platform & Architecture

• Design and implement cloud-based data lake / warehouse architectures centered around modern platforms (e.g., Snowflake)
• Develop data ingestion pipelines from enterprise systems (project management, ERP, HR systems, contract databases)
• Build structured and unstructured ingestion workflows using Python, REST APIs, ETL tools, and serverless compute (e.g., AWS Lambda)
• Establish best practices for data governance, cataloging, lineage, and security

Generative AI & LLM Systems

• Develop retrieval-augmented generation (RAG) pipelines using enterprise document datasets
• Implement embedding strategies and manage vector databases (e.g., Pinecone or similar)
• Enable semantic search, document indexing, and corpus-level comparison workflows
• Build agent-based workflows using modern LLM orchestration frameworks (e.g., LangChain or similar ecosystems)
• Define prompt management practices, evaluation frameworks, and safety guardrails

MLOps & Production Systems

• Deploy machine learning models and pipelines in cloud environments (AWS, Azure, or similar)
• Build CI/CD pipelines for ML workflows and data pipelines
• Implement monitoring, drift detection, and automated retraining processes
• Design systems for scalability, reliability, and high availability

Required Experience & Skills

• 8 years in data engineering, machine learning engineering, or related fields
• Strong proficiency in Python (production-level development)
• Experience with modern cloud data platforms (e.g., Snowflake or equivalents)
• End-to-end experience building and deploying ML pipelines in production
• Advanced SQL and data modeling expertise
• Hands-on experience with LLM APIs and ecosystems (e.g., OpenAI, Claude, Gemini)
• Experience building RAG systems and working with vector databases (e.g., Pinecone)
• Familiarity with cloud platforms (AWS, Azure, or similar)
• Experience implementing CI/CD pipelines for data and ML systems
• Strong understanding of data security and enterprise architecture

Nice to have:

• Experience developing RESTful APIs and backend services
• Experience building modern web applications (React, Next.js, or similar)