Artificial intelligence Engineer - Vice President

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 role is ideal for 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 the ability to operate as a force multiplier for the team. 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. Responsibilities Lead the architecture and delivery of production AI systems, including document intelligence (IDP), intelligent knowledge systems, and agentic orchestration, to power internal and external 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. 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 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 production AI/ML systems, including hands-on experience with AWS or cloud-native development patterns for AI/ML workloads and a demonstrated track record of delivering complex systems from inception through production. Strong proficiency in Python and demonstrated ability to build well-engineered, maintainable software, including adherence to software engineering best practices (source control, CI/CD, testing, and documentation). Deep expertise in at least one of the following: LLM-based systems (fine-tuning, inference optimization, prompt engineering, modern AI tooling such as transformers, vLLM, or agentic frameworks), document intelligence and IDP, or ML system design (training pipelines, model serving, evaluation infrastructure). Experience designing and operating end-to-end ML pipelines in production, including model training, deployment, monitoring, and iteration (MLOps). Solid fundamentals in statistics, experimentation, and data quality with the ability to reason rigorously about metrics, error patterns, and the limitations of AI systems. Experience leading technical design, mentoring engineers, and driving architectural decisions within a team. Strong written and verbal communication skills to represent the team in cross-functional settings, document technical designs, and communicate effectively with both technical and non-technical stakeholders. Experience spanning more than one of LLM systems, document intelligence, and ML platform and infrastructure. Familiar with agentic architectures and protocols (e.g., MCP and A2A) or designing multi-step, tool-using AI workflows. Knowledge of cost and latency optimization for LLM inference at scale (quantization, batching strategies, and model routing). Prior experience in financial services or FinTech, particularly in document-heavy or compliance-sensitive domains. Contributions to open-source projects or published technical writing demonstrating thought leadership in applied AI. Benefits The base salary range for this role is $170,000 to $200,000. 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 including 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). Employees will work in the office Monday-Thursday, with flexibility to work remotely on Friday. 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 legally protected characteristics. #J-18808-Ljbffr iCapital