Artificial Intelligence Forward Deployment Engineer - Associate

iCapital is powering the world’s alternative investment marketplace. Our financial technology platform has transformed how advisors, wealth management firms, asset managers, and banks evaluate and recommend bespoke public and private market strategies for their high-net-worth clients. iCapital services, approximately $945 billion in global client assets invested in 1,940 funds, as of June 2025. iCapital has been named to the Forbes Fintech 50 for seven consecutive years (2018-2024); a three-time selection by Forbes to its list of Best Startup Employers (2021-2023); and a four-time winner of MMI/Barron’s Solutions Provider award (See link below). About the Role iCapital is seeking a Forward Deployment AI Engineer (FDE) to accelerate the delivery of production-grade AI capabilities into real business workflows. This role is ideal for an engineer who thrives at the intersection of engineering, solution design, and stakeholder partnership. The ideal candidate can take ambiguous requirements, rapidly build working solutions, deploy them safely into production environments, and iterate based on real-world usage. On the AI/ML team, this individual will work closely with AI/ML engineers, Product and Business Partners, and downstream Technology teams to embed AI systems directly into day-to-day operations using platforms such as Copilot Studio, Power Automate, and other agentic solutions. This role is expected to combine strong technical execution with crisp communication, operational discipline, and a bias toward measurable business impact. Responsibilities Own forward deployment end-to-end for AI-powered solutions (i.e. discovery, scoping, prototyping, integration, production rollout, monitoring, and iteration) based on outcomes. Partner with stakeholders to translate business problems into deployable solutions such as running working sessions, clarifying requirements, defining success metrics, and managing tradeoffs to drive adoption. Integrate agentic workflows and capabilities into business systems, orchestrating tools, automations, and decision flows to support end to end AI driven processes. Drive project execution for AI deployments, including workplan definition, milestone tracking, dependency and risk management, stakeholder communication, and launch coordination across engineering, product, and business teams. Establish measurement and feedback loops, instrumenting workflows to track quality, throughput, and business KPIs, and using those signals to drive continuous improvement post-launch. Debug and resolve production issues spanning model behavior, data quality, automation logic, and system integrations and coordinate across teams to root-cause and remediate issues quickly. Document and enable through clear handoffs, reference architectures, and internal documentation for both technical and non-technical audiences. Qualifications 3-6+ years of experience delivering production software or applied AI systems into real operational environments Proven experience leveraging AI to automate, orchestrate, and scale operational processes Strong proficiency in Python, with the ability to integrate custom services into broader enterprise workflows Experience with cloud-native development patterns (i.e. AWS), including deployment, monitoring and observability, and best operational practices Demonstrated ability to work through ambiguous problem statements, structure discovery, and deliver solutions with measurable business impact Strong written and verbal communication skills and comfort working directly with business stakeholders Hands-on experience building solutions with Copilot Studio, Power Automate, or other agentic solutions, especially for AI-driven workflow automation and agent-based interactions Familiar with enterprise integration patterns (i.e. service-to-service auth, eventing, APIs, data contracts) and operating AI systems in regulated environments Strong operational mindset such as logging, monitor ... (truncated, view full listing at source)