The Opportunity

A well-capitalized investment organization is building out a forward-deployed AI engineering function to directly support senior stakeholders across its portfolio. This is a high-visibility individual contributor role embedded at the intersection of enterprise AI, data infrastructure, and operational transformation.

You will be building production-grade systems, working directly with C-suite stakeholders, and driving measurable outcomes across finance, revenue, and operations functions. The organization is making significant investment in AI infrastructure right now, and this hire is central to that buildout.

What You'll Be Doing

Data Platform & Architecture

Design and implement cloud-based data lake and warehouse architectures on modern platforms such as Snowflake
Build data ingestion pipelines from enterprise systems including ERP, HR, contract management, and project management tools
Develop structured and unstructured ingestion workflows using Python, REST APIs, ETL tooling, and serverless compute (AWS Lambda or equivalent)
Establish best practices around data governance, cataloging, lineage, and security

Generative AI & LLM Systems

Build retrieval-augmented generation (RAG) pipelines using enterprise document datasets
Implement embedding strategies and manage vector databases (Pinecone or equivalent)
Enable semantic search, document indexing, and corpus-level comparison workflows
Develop agent-based workflows using LLM orchestration frameworks such as LangChain
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 and maintain CI/CD pipelines for ML and data workflows
Implement monitoring, drift detection, and automated retraining processes
Design for scalability, reliability, and high availability from the start

Application Development & AI Interfaces

Build internal web applications and dashboards that expose AI/ML outputs to business users
Develop interactive analytical tools including risk visualizations, scenario modeling, and milestone tracking
Create chatbot and AI assistant interfaces for enterprise knowledge access
Integrate backend ML services into secure, scalable, user-facing applications

What We're Looking For

5 to 10 years of experience in data engineering, machine learning engineering, or a closely related field
Production-level Python development
Hands-on experience with modern cloud data platforms (Snowflake or equivalent)
End-to-end experience building and deploying ML pipelines in production environments
Advanced SQL and data modeling skills
Direct experience with LLM APIs (OpenAI, Claude, Gemini, or similar)
Experience building RAG systems and working with vector databases
Familiarity with AWS, Azure, or comparable cloud infrastructure
CI/CD implementation experience for data and ML systems
Experience developing RESTful APIs and backend services
Comfort building modern web applications (React, Next.js, or similar)
Background from high-engineering-bar environments strongly preferred, including hyperscalers, frontier AI companies, or management consulting with deep technical delivery

A Note to Third-Party Recruiters, Bench Recruiters, and C2C/Independent Contractor Vendors

This role is being managed exclusively through The Phoenix Group. Submissions from outside recruiting agencies, C2C arrangements, independent contractors, or any third-party staffing intermediaries will not be reviewed under any circumstances.

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.