Core AI Platform Engineer - Assistant Vice President

icapitalnetwork; New York (NY); On-site; USD 120,000 - 170,000; Full time

Benefits offered by this job

Equity

Annual bonus

Health insurance

Retirement plan

Job summary

iCapital is seeking an Assistant Vice President AI Engineer to design, develop, and deliver production-grade AI systems that drive measurable business outcomes across the firm. This role combines deep technical expertise with cross-functional partnership to ship complex AI solutions at scale.

The ideal candidate will own AI projects end-to-end, contribute to architecture, and ensure reliability, scalability, and measurable impact while mentoring junior engineers and reducing technical debt.

Qualifications

• 5+ years of experience deploying production AI/ML systems on cloud platforms.
• Strong Python and software engineering practices (CI/CD, testing, docs).
• Proven experience with LLMs, agents, RAG, and conversational AI.
• End-to-end ML pipelines: training, deployment, monitoring, evaluation.
• Excellent communication and cross-functional collaboration.
• Financial services/FinTech exposure preferred.
• Open-source contributions or publications preferred.

Responsibilities

• Design and deliver production AI systems powering processes and automation.
• Own AI projects end-to-end from scoping to deployment and monitoring.
• Contribute to technical design and architectural decisions.
• Develop evaluation frameworks, metrics, datasets, and versioning.
• Partner with Product, Ops, Legal, and Business teams to translate requirements.
• Mentor junior engineers and improve team processes.

Skills

Python

AI/ML systems

Documentation

CI/CD

Communication

Tools

AWS

LLM frameworks

RAG

Git

Job description

Artificial Intelligence Engineer - Assistant Vice President

About the Role

iCapital is seeking an Assistant Vice President Artificial Intelligence Engineer to design, develop, and deliver production-grade AI systems that drive measurable business outcomes across the firm. This role is expected to bring sound judgment on technical approach, a bias toward delivery, and able to translate ambiguous business needs into well-scoped, well-executed solutions. The ideal candidate is an experienced, hands-on engineer with a track record of shipping complex AI systems end-to-end and someone who combines deep technical expertise with strong cross-functional partnership, architectural judgment, and able to operate as a force multiplier for the team. This individual will own AI projects and defined workstreams, contribute to system design and technical decisions, partnering directly with business stakeholders, and ensuring that AI capabilities are built to production-grade standards of reliability, scalability, and measurability.

Responsibilities

• Design and deliver production AI systems, including document intelligence (IDP), intelligent knowledge systems, agentic orchestration, conversational AI, and generative AI applications, to power internal and external business processes, digital experiences, and workflow automation at scale.
• Own AI projects end-to-end, from problem scoping and stakeholder alignment through solution design, implementation, deployment, monitoring, and continuous improvement, delivering tangible business outcomes with a track record of consistent, high-quality delivery.
• Contribute to technical design and architectural decisions for the team, including API design, system decomposition, evaluation strategy, and infrastructure patterns, following and contributing to team engineering standards across the AI/ML platform.
• Develop and apply robust evaluation frameworks for AI systems, defining statistically sound, problem-specific metrics, curating benchmark datasets, and enforcing strict versioning to ensure reproducibility and continuous improvement.
• Partner directly with cross-functional stakeholders, including the Product, Operations, Legal, and Business teams, to identify AI opportunities, translate requirements into technical plans, and communicate tradeoffs, risks, and recommendations clearly.
• Support and mentor junior engineers on the team through code review, design review, pair problem-solving, and knowledge sharing, acting as a technical role model and raising the overall capability of the group.
• Identify systemic problems and propose solutions, proactively improving team processes, tooling, and infrastructure to reduce technical debt and increase development velocity.

Qualifications

• 5+ 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 and tooling
• 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 contributing to technical architecture and design discussions, conducting code and design reviews, and mentoring or supporting the growth of other engineers
• Excellent written and verbal communication skills, with the ability to document technical solutions, partner effectively with cross-functional stakeholders, and communicate complex concepts to both technical and non-technical audiences
• 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

Benefits

The base salary range for this role is $120,000 to $170,000.

iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, v