Vice President, AI Platform Architect — Production AI

icapitalnetwork; New York (NY); On-site; USD 170,000 - 210,000; Full time

Benefits offered by this job

Equity

Annual bonus

Job summary

iCapital seeks a Vice President Artificial Intelligence Engineer to lead the design, development, and delivery of production-grade AI systems that drive measurable business outcomes across the firm.

You will own key workstreams, mentor engineers, and partner with stakeholders to ensure AI capabilities meet reliability, scalability, and measurable standards, translating complex business needs into well-scoped solutions.

Qualifications

• 7+ years of experience developing and deploying production AI/ML systems, including cloud-native solutions on AWS or similar platforms, with a proven track record of delivering complex applications from design through production
• Strong proficiency in Python and software engineering best practices, including source control, CI/CD, testing, documentation, and the development of scalable, maintainable software
• Deep expertise building production AI solutions, including LLM applications, AI agents, retrieval-augmented generation (RAG), conversational AI, document intelligence, and agentic workflows, with hands‑on experience using modern AI frameworks, tooling, and protocols such as MCP and A2A
• Experience designing, deploying, and operating end‑to‑end machine learning pipelines, including model training, deployment, monitoring, evaluation, and continuous improvement in production environments
• Strong foundation in statistics, experimentation, data quality, and AI system evaluation, with experience developing benchmarks, defining performance metrics, analyzing errors, and optimizing systems for accuracy, reliability, scalability, cost, and latency
• Experience leading technical design and architectural decisions, conducting code and design reviews, mentoring engineers, and driving engineering excellence across teams
• Excellent written and verbal communication skills, with the ability to document technical solutions, collaborate with cross‑functional stakeholders, and communicate complex concepts to both technical and non‑technical audiences
• Experience spanning multiple AI domains, including LLM systems, document intelligence, and ML platforms or infrastructure
• Experience in financial services or FinTech, particularly within document‑heavy, regulated, or compliance‑sensitive environments is preferred
• Contributions to open‑source projects, technical publications, conference presentations, patents, or other demonstrated thought leadership in applied AI and machine learning is preferred

Responsibilities

• Lead the architecture and delivery of production AI systems across IDP, knowledge systems, and agentic orchestration at scale
• Own AI projects end-to-end, from problem scoping and stakeholder alignment through solution design, implementation, deployment, monitoring, and continuous improvement
• Drive technical design and architectural decisions for APIs, system decomposition, evaluation strategy, and infrastructure patterns
• Architect and champion robust evaluation frameworks for AI systems, defining statistically sound metrics, curating benchmark datasets, and enforcing versioning
• Partner with cross-functional stakeholders to identify AI opportunities, translate requirements into technical plans, and communicate tradeoffs, risks, and recommendations clearly
• Mentor and develop engineers through code reviews, design reviews, pair problem-solving, and knowledge sharing
• Identify systemic problems and propose solutions, proactively improving team processes, tooling, and infrastructure to reduce technical debt and increase velocity

Skills

AI systems

Python

Cloud-native

CI/CD

Architectural design

Mentoring

Cross-functional collaboration

Communication

Tools

AWS

MCP

A2A

APIs

Job description

iCapital seeks a Vice President Artificial Intelligence Engineer to lead the design, development, and delivery of production-grade AI systems that drive measurable business outcomes across the firm.

You will own key workstreams, mentor engineers, and partner with stakeholders to ensure AI capabilities meet reliability, scalability, and measurable standards, translating complex business needs into well-scoped solutions.