Job description

Artificial Intelligence Engineer - Vice President Department: Software Engineering About the Role iCapital is seeking 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. This individual will own key workstreams and serve as a technical leader, driving system design, mentoring engineers, partnering directly with business stakeholders, and ensuring that AI capabilities are built to production-grade standards of reliability, scalability, and measurability. The ideal candidate is a seasoned 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 role is expected to bring independent judgment on a technical approach, a bias toward delivery, and able to translate ambiguous business needs into well-scoped, well-executed solutions. Responsibilities Lead the architecture and delivery of 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. Drive technical design and architectural decisions for the team, including API design, system decomposition, evaluation strategy, and infrastructure patterns, establishing standards that raise the quality bar across the AI/ML platform. Architect and champion 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. Mentor and develop 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 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 Benefits The base salary range for this role is $170,000 to $210,000. 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, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO). We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday. For additional information on iCapital, please visit icapitalnetwork.com Twitter: @icapitalnetwork | LinkedIn: linkedin.com | Awards Disclaimer: icapitalnetwork.com iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

Requirements

Must-haves

Artificial Intelligence Engineer - Vice President
Department: Software Engineering
Mentor and develop 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.
Strong proficiency in Python and software engineering best practices, including source control, CI/CD, testing, documentation, and the development of scalable, maintainable software
Experience designing, deploying, and operating end-to-end machine learning pipelines, including model training, deployment, monitoring, evaluation, and continuous improvement in production environments
Experience leading technical design and architectural decisions, conducting code and design reviews, mentoring engineers, and driving engineering excellence across teams
Experience spanning multiple AI domains, including LLM systems, document intelligence, and ML platforms or infrastructure

Nice-to-haves

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

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Keywords to mirror

aiapimlawspythonci/cdllmmachine learning

Platform: greenhouse
Effort: quick

Benefits

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Dental

Vision

Pto

Paid Time Off

Parental Leave