AI Enablement Engineer

Team Overview

The Applied AI (AI Enablement) team is a newly formed, strategic function focused on accelerating enterprise-wide adoption of generative AI technologies. We build the foundational infrastructure, tools, and expertise that enable teams across the organization to leverage AI effectively and responsibly.

Role Summary

We're seeking an AI Enablement Engineer to join our team in building, deploying, and scaling AI solutions across the enterprise. You'll work at the intersection of machine learning engineering, data engineering, and platform operations—building RAG systems, evaluating cutting-edge LLM models, and serving as a trusted advisor to business units and corporate functions navigating their AI adoption journey.

Key Responsibilities

AI Infrastructure & Model Development

• Design, build, and optimize Retrieval-Augmented Generation (RAG) systems for various enterprise use cases
• Develop and maintain data ingestion pipelines (Python and other scripting languages) to populate and manage vector databases
• Deploy and maintain AI infrastructure including Amazon Bedrock and Ollama environments
• Implement evaluation frameworks and tooling (such as LLMComparator) to systematically compare LLM performance across different models and use cases

Model Evaluation & Selection

• Conduct rigorous evaluations of LLM models for diverse applications including RAG, coding agents, and domain-specific tasks
• Establish benchmarking standards and best practices for model selection
• Stay current with the rapidly evolving LLM landscape and provide recommendations on emerging capabilities

Enterprise AI Enablement & Consulting

• Partner with teams, business units, and corporate functions to assess their AI needs and design appropriate solutions
• Provide guidance on build vs. buy decisions—advising when third-party GenAI tools are appropriate versus when internal capabilities should be leveraged
• Enable teams in adopting AI-assisted development tools including Claude Code, Cursor, and GitHub Copilot
• Develop documentation, training materials, and best practices for enterprise AI adoption

Platform Operations

• Ensure reliability, performance, and cost-effectiveness of AI infrastructure and services
• Monitor and optimize vector database performance and model inference costs
• Collaborate with security and compliance teams to ensure responsible AI deployment

Required Qualifications

• 6+ years of experience in any of the following:  Site reliability engineering (SRE), Software engineering, Data engineering (DBA/DBRE), or Machine learning engineering
• Strong proficiency in Python and experience building data pipelines
• Hands-on experience with LLMs and understanding of prompting techniques, fine-tuning, and RAG architectures
• Experience with vector databases (e.g., Pinecone, Weaviate, pgvector, ChromaDB)
• Familiarity with cloud platforms, particularly AWS services
• Excellent communication skills with ability to explain technical concepts to non-technical stakeholders
• Demonstrated ability to work independently and drive projects from concept to production

Preferred Qualifications

• Experience with Amazon Bedrock, SageMaker, or similar managed ML services
• Familiarity with Ollama or other local LLM deployment frameworks
• Background in evaluating and benchmarking ML models
• Experience with AI-assisted coding tools (Claude Code, Cursor, GitHub Copilot, etc.)
• Understanding of MLOps practices and tools
• Previous consulting or internal enablement experience
• Knowledge of responsible AI practices and governance frameworks

What You'll Bring

• Technical versatility: Comfort moving between infrastructure work, model evaluation, and application development
• Consultative mindset: Ability to understand business problems and translate them into technical solutions
• Rapid learning: The AI landscape evolves quickly—you stay curious and adapt
• Pragmatism: You balance innovation with practical delivery and know when "good enough" is the right answer
• Collaboration: You enjoy partnering with diverse teams and building relationships across the organization

What We Offer

• Opportunity to shape AI strategy and adoption at the enterprise level
• Work with cutting-edge AI technologies and tools
• High-visibility role with exposure to leadership and diverse business units