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Salary: USD 120,000 - 170,000 / annual
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 is a hands-on technical leadership role combining deep AI expertise with cross-functional partnership and architectural judgment.
You will own AI projects and defined workstreams end-to-end, from problem scoping through deployment and continuous improvement. Key responsibilities include:
• 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, 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.
• 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.
• Partner directly with cross-functional stakeholders including Product, Operations, Legal, and Business teams to identify AI opportunities, translate requirements into technical plans, and communicate tradeoffs and risks.
• Support and mentor junior engineers through code review, design review, pair problem-solving, and knowledge sharing, acting as a technical role model.
• Identify systemic problems and propose solutions to improve team processes, tooling, and infrastructure.
The role is based in New York with a hybrid schedule: in-office Monday–Thursday, remote on Friday.
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 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
