Helping Financial Advisors and Wealth Managers incorporate alternative strategies at scale. Helping Asset Managers open new lanes of distribution.
About the role
iCapital is seeking an Associate AI Engineer to help build and scale production-grade AI systems that deliver real business outcomes. This role is ideal for an engineer early in their career who enjoys turning ambiguous problem statements into working systems, and who pairs creative problem-solving with disciplined measurement, reproducibility, and operational rigor. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Strong proficiency in Python
- Solid fundamentals in statistics, exploratory data analysis, and the ability to reason about data quality, experiments, and error patterns
- Clear written and verbal communication with the ability to document work and collaborate in a team setting
- Experience with modern LLM tooling (i.e. transformers, unsloth, vLLM, agentic frameworks) or document AI approaches (IDP)
- Familiar with software development best practices (source control, CI/CD, testing, documentation) and working through a full development lifecycle
- Experience with various agentic communication protocols, (i.e. MCP, A2A) is a plus
More about this role
iCapital is seeking an Associate AI Engineer to help build and scale production-grade AI systems that deliver real business outcomes. This role is ideal for an engineer early in their career who enjoys turning ambiguous problem statements into working systems, and who pairs creative problem-solving with disciplined measurement, reproducibility, and operational rigor. This individual will be on the AI/ML team and will work closely with senior AI and machine learning engineers, as well as cross-functional partners, to design, implement, evaluate, and operate AI capabilities as APIs and services in a real-world FinTech environment. This individual will be expected to bring strong analytical fundamentals, curiosity, and a bias toward delivering robust, maintainable systems.
- Design and implement modular AI capabilities including LLM-based reasoning, document intelligence (OCR/IDP), intelligent knowledge systems, and agentic orchestration to power internal and external workflow automation.
- Own components of the full AI system life cycle to achieve tangible business outcomes, including scoping, POC, solution design, model development, deployment, monitoring and continuous improvement...
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