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Applied AI Engineer
Job Summary
Join an early-stage AI platform transforming financial workflows by implementing cutting-edge research into production systems. You'll build agentic AI, retrieval pipelines, and knowledge graphs to surface critical insights from unstructured data like PDFs and emails. This role offers hands-on impact, rapid iteration with customer feedback, and ownership of end-to-end AI deployment in a high-growth environment.
Essential Functions
- Implement and adapt cutting-edge AI research to build systems that understand financial context and business concepts
- Design retrieval pipelines that extract and synthesize insights from unstructured sources with intelligent conflict resolution
- Build agentic workflows that enable AI systems to reason about financial relationships, perform benchmarking, and conduct comparative analysis
- Construct and maintain knowledge graphs that capture complex financial relationships, entity connections, and market dynamics
- Create evaluation frameworks to measure and improve AI performance across investment research, due diligence, and portfolio monitoring
- Design systems that maintain traceability from AI outputs to primary sources
- Experiment with latest LLM orchestration patterns and context management techniques for financial use cases
- Deploy and operate production systems end-to-end with ownership over reliability, performance, and maintainability
Required Qualifications
- 3+ years of experience in machine learning, AI research, or applied AI engineering
- Strong background in LLMs, RAG systems, and agentic AI workflows
- Experience designing evaluation frameworks and benchmarks for AI systems
- Interest or understanding of financial markets, investment processes, or quantitative finance
- Experience with retrieval systems, embeddings, and multi-modal data processing
- Entrepreneurial mindset with ability to translate cutting-edge research into practical business value
Preferred Qualifications
- Publication record or demonstrated expertise in relevant AI research areas
- Experience as a full-stack engineer (React/TypeScript + Python/Node or similar)
- Experience at an early-stage, high-growth startup
- Degree from a top CS program
- Research publications in relevant areas
Technical Skills
- LLMs
- RAG systems
- Agentic AI workflows
- Retrieval systems
- Embeddings
- Knowledge graphs
- Evaluation frameworks
- Multi-modal data processing
- LLM orchestration
- Context management
Education & Certifications
Degree from a top CS program preferred. Research publications in relevant AI areas are a plus.
Compensation & Benefits
Competitive salary range of $150,000 - $300,000 based on experience, plus equity in an early-stage startup.