Artificial Intelligence Engineer

AI Platform Engineer

A technology focused role within a large, data-driven organization seeking an experienced engineer to build and scale modern AI, data, and application platforms. The position focuses on developing production-grade systems across data engineering, machine learning, and generative AI, while supporting enterprise-wide technology initiatives.

Fully on site in NYC

Comp range- $250K base and 30-50% bonus

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

Application Development & AI Interfaces

• Develop internal web applications and dashboards to expose AI/ML outputs
• Build interactive analytical tools (e.g., risk visualizations, milestone tracking, scenario modeling)
• Create chatbot and AI assistant interfaces for enterprise knowledge access
• Integrate backend ML services into scalable user-facing applications
• Ensure secure, responsive, and user-friendly front-end experiences

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

Core Technical Skills:

Data Engineering

ML Pipelines

Cloud Platforms (AWS, Azure)

Data Governance

ETL & Data Ingestion

Serverless Computing

Vector Databases (Pinecone)

Generative AI & LLM APIs

MLOps & CI/CD

API Development

The role leads the development of scalable AI and data infrastructure that enhances operational efficiency and enterprise AI integration.

The Phoenix Group Advisors is an equal opportunity employer. We are committed to creating a diverse and inclusive workplace and prohibit discrimination and harassment of any kind based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We strive to attract talented individuals from all backgrounds and provide equal employment opportunities to all employees and applicants for employment.