The Role
The Founding AI Engineer will develop Vantager's AI-native platform, optimize financial task performance using LLMs, and improve AI systems through instrumentation and data processing.
Summary Generated by Built In
About Vantager
At Vantager, we're shaping the future of global capital allocation. We're building an AI-native platform that redefines how investors interact with private market financial data, areas traditionally challenged by unstructured data and limited regulation. We're on a high-growth trajectory, VC backed by world-class investors and unicorn fintech founders. Our platform is already empowering over 20 investment firms, collectively managing more than $100B in assets, to work faster through workflow automation and make smarter, data-driven decisions.
Our mission is bold, our technology cutting-edge, and our team is the driving force behind our success. We believe in the power of innovation, the importance of integrity, and the necessity of a collaborative environment. Our culture fosters creativity and encourages each individual to take ownership of their work. Here, every idea matters, and every contribution counts.
What we're looking for
Vantager is seeking a passionate and experienced Founding AI Engineer. This role is perfect for a self-driven software engineer who's excited about large language models and ready to make a significant impact in the investment space. At Vantager, you'll work alongside some of the brightest minds in the industry, tackling challenging problems and making a real impact.
If you're passionate about the intersection of AI and financial data, and eager to grow in a dynamic and supportive environment, Vantager is the place for you. We're looking for independent and ambitious talent who are ready to push the boundaries of what's possible and redefine the investment landscape. Join us, and together, let's build something extraordinary.
Responsibilities
- Architect and develop our AI-native platform, taking ownership of key product features
- Work directly with the CEO and CTO on critical product and technology decisions
- Deliver best-in-class financial task performance via LLM and RAG system optimization
- Implement a systematic approach to instrument, observe, and continuously improve our AI systems, including designing evaluation metrics and testing infrastructure
- Experiment with and lead the development of retrieval systems for efficient ingestion, processing, and generation of both structured and unstructured financial data
- Stay at the forefront of AI advancements, continuously improving our platform's capabilities and identifying new application areas within the investment process
Qualifications
- 3+ years of software engineering experience, with strong proficiency in our tech stack: Python, FastAPI, relational databases (MySQL/Postgres), and TypeScript
- Proven track record in building, deploying, and iteratively improving LLM applications
- Deep understanding of AI and RAG concepts, including: prompting, retrieval systems, structured output, vector databases, embedding models, and LLM fine-tuning techniques
- Proven experience in designing and managing data pipelines, including ETL processes
- Interest in developing document search systems for efficient data retrieval
- Self-motivated with excellent problem-solving and communication skills
Bonus Points
- Degree from a top-tier university in Computer Science, AI, or a related field
- Experience in the finance, trading, or investment sectors
- Knowledge of data science, financial analysis, and related fields
- Familiarity with cloud platforms (AWS), serverless architecture, and Docker
- Previous experience at a startup or small-mid sized company
- Contributions to open-source projects
Compensation
- $100k - $200k salary
- 0.5% - 1.5% equity
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The Company
What We Do
Vantager is an AI-powered platform that streamlines pre-investment due diligence, analysis, and reporting processes for institutional private markets and Limited Partners (LPs), using AI and OCR to classify and link document information for easier data sourcing.









