The job, in the employer's words
This role supports the ongoing delivery of agentic AI–enabled automation across document-heavy and operational workflows. The intent is to move critical automation work off a high-cost contractor and into a lower-cost, full-time role without losing execution capability or momentum.
The focus is on building and supporting automation. This is hands-on delivery work that is well understood, repeatable, and already embedded in core operational processes.
Responsibilities:
- Assist in building and enhancing agentic AI workflows that automate multi-step processes such as document intake, data extraction, validation, enrichment, and downstream routing.
- Support integration of AI / ML and LLM-based models for document classification, entity extraction, and metadata generation, and connect those outputs into end-to-end automated workflows.
- Build and maintain automation workflows and system integrations across document platforms, workflow engines, and operational systems.
- Assist with API integrations and data movement, ensuring secure, reliable flow between platforms with appropriate controls and auditability.
- Support production automation by monitoring workflows, troubleshooting failures, addressing defects, and improving reliability through logging, retries, and validation checks.
- Work closely with Product, Engineering, and Operations to translate known business requirements into implemented automation and to support ongoing enhancements.
- Contribute to documentation and standards so workflows are maintainable and not dependent on contractor knowledge.
Qualifications:
- 6+ years of experience in data science, machine learning or AI-related roles, with 3+ years leading cross-functional initiatives at scale
- Experience operationalizing AI/ML or advanced analytics solutions in production, ideally within financial services, fintech, or data-driven platforms
- Strong understanding of LLMs, data science, AI/ML, and modern AI architectures, including model evaluation, context engineering, and agentic workflow automation
- Experience designing and implementing agentic AI workflows, including multi-step AI agents that automate complex processes and integrate with enterprise systems, data, and APIs
- Experience building or supporting production automation, ideally in document-heavy or regulated environments.
- Hands-on exposure to AI-driven data extraction, document processing, or NLP-based workflows.
- Familiarity with workflow orchestration, rules-based automation, and system integrations.
- Comfortable working within established patterns and under technical direction.
- Execution-oriented, able to support existing platforms and improve them incrementally.
We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office four days, with the flexibility to work remotely one day (Friday).
For additional information on iCapital Network, please visit https://www.icapitalnetwork.com/about-us Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc
Requirements mentioned
- 6+ years of experience in data science, machine learning or AI-related roles, with 3+ years leading cross-functional initiatives at scale
- Experience operationalizing AI/ML or advanced analytics solutions in production, ideally within financial services, fintech, or data-driven platforms
- Strong understanding of LLMs, data science, AI/ML, and modern AI architectures, including model evaluation, context engineering, and agentic workflow automation
- Experience designing and implementing agentic AI workflows, including multi-step AI agents that automate complex processes and integrate with enterprise systems, data, and APIs
- Experience building or supporting production automation, ideally in document-heavy or regulated environments.
- Hands-on exposure to AI-driven data extraction, document processing, or NLP-based workflows.
- Familiarity with workflow orchestration, rules-based automation, and system integrations.
- Comfortable working within established patterns and under technical direction.
- Execution-oriented, able to support existing platforms and improve them incrementally.
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