AI Engineer (Vice President)

Join ICapital as a Vice President Artificial Intelligence Engineer, where you will lead the design, development, and delivery of production-grade AI systems that drive measurable business outcomes. You will own key workstreams, serve as a technical leader, and partner directly with business stakeholders. The ideal candidate has 7+ years of experience in developing and deploying production AI/ML systems, strong proficiency in Python, and experience in financial services or FinTech.

• Lead the architecture and delivery of production AI systems, including document intelligence, intelligent knowledge systems, agentic orchestration, conversational AI, and generative AI applications.
• 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 the team, including API design, system decomposition, evaluation strategy, and infrastructure patterns.

• 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
• Experience spanning multiple AI domains, including LLM systems, document intelligence, and ML platforms or infrastructure
• Experience leading technical design and architectural decisions, conducting code and design reviews, mentoring engineers, and driving engineering excellence across teams
• Experience in financial services or FinTech, particularly within document-heavy, regulated, or compliance-sensitive environments is preferred
• 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
• 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
• Contributions to open-source projects, technical publications, conference presentations, patents, or other demonstrated thought leadership in applied AI and machine learning is preferred
• 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