Remote AI Engineer

SaxeCap is the premier AI transformation and investment platform in private equity. We created the concept of buying out traditional businesses and transforming them with AI in 2018, and today we are the go-to AI transformation partner for 60+ PE firms globally, including 9 of the top 10 by AUM and the world's leading sovereign wealth funds. We've transformed 140+ businesses across healthcare services, business services, financial services, software, consumer, and more, driving billions of dollars of enterprise value expansion along the way. We operate at the intersection of three businesses: a private equity investment arm, an in-house AI transformation firm that designs and deploys bespoke GenAI, ML, and automation solutions, and a suite of proprietary software products. Our team comes from places like Google, Palantir, Meta, Surge AI, Blackstone, TPG, Cerberus, Millenium, Balyasny, McKinsey, Bain, Oliver Wyman, MIT, Stanford, GSB, HBS, and Wharton. Our leadership includes early investors in OpenAI, Anthropic, Groq, SpaceX, Neuralink, Mercor, Lambda Labs, etc. But what makes our team exceptional isn't where they came from or what they've invested in, it's what they ship. We are hiring a Forward Deployed AI Engineer to join our AI transformation team. This is not a typical software engineering role. You will be building and deploying AI solutions across dozens of companies, industries, and problem domains, working directly with clients and PE sponsors to solve their highest-value business problems with production-grade GenAI, ML, and automation. In a given month, you might build a RAG system that automates a core operational workflow for a healthcare services company, deploy an ML model that optimizes pricing for a financial services platform, architect a data pipeline that unlocks analytics capabilities for a business that has never had them, and mentor junior engineers on the team through all of it. You will be in the room with executives and PE partners, translating business problems into technical architectures, then building and shipping the solutions yourself. If you want to be the best AI engineer in the world, there is no faster way to get reps across industries, problem types, and AI techniques than this role.

You are an engineer who builds fast, ships to production, and cares about business outcomes, not just technical elegance. 3+ years of experience building and deploying software products end to end (design, implementation, testing, deployment, maintenance) ~ Expert in Python (Django, Flask, FastAPI, Pandas, etc.) and/or JavaScript (React, Node). These are our primary languages and you should be deeply fluent in at least one. ~ Strong experience with SQL, data modeling, and cloud infrastructure (AWS, GCP, or Azure) ~ Hands-on experience with generative AI: you have built RAG systems, AI agents, prompt engineering pipelines, fine-tuned models, or similar. Experience with data engineering, integrations, ETL/ELT pipelines, and working with messy, real-world data ~ Experience with data science and ML: NLP, recommender systems, classification, regression, neural networks. You don't need to be a research scientist, but you should be comfortable selecting, training, and deploying models. ~ You know what it means to deploy, monitor, debug, and maintain software that real users depend on. ~ S. in Computer Science, Engineering, or a related technical field ~ You have shipped AI systems that real users and real businesses depend on. You've worked across multiple problem areas and can context-switch without losing quality. Full-stack AI fluency.

You build the data pipelines that feed them, the APIs that serve them, the frontends that expose them, and the monitoring that keeps them running. Open-source contributions, side projects, hackathon wins, or a startup attempt. You build things because you can't help it.

You will get more reps across AI techniques, industries, and business problems in one year at SaxeCap than in five years at a typical tech company.