Product Manager, Client Solutions

Design and deliver AI-powered workflows on FactualIQ’s enterprise Decision Engine. Translate complex client needs into scalable solutions, shape product strategy, and drive hands-on delivery of intelligent systems that accelerate decision-making for enterprise clients.

As a Product Manager, you will work directly with clients to design, develop, and deliver AI-powered workflows built on FactualIQ’s Decision Engine. You will translate complex decision and data requirements into software product specifications, drive workflow design, configure tools and components, and ensure solutions integrate securely and reliably into clients’ strategic decision‑making systems. This is a hybrid product management and solutions delivery role where you’ll own both the strategic shaping of client solutions and the hands‑on configuration and validation work required to bring them to production.

You’ll work alongside engineering, data science, and client success teams, building expertise in enterprise AI solution delivery as FactualIQ scales its client base and solution portfolio.

• Participate in early-stage client conversations by contributing to solution outlines, scoping guidance, and technical input during pre-sales activities.
• Partner directly with clients to identify high-value use cases, define scope, and shape phased solutions aligned to FactualIQ’s platform capabilities.
• Represent the voice of users by grounding solution design in real decision workflows and client systems to promote successful long-term adoption.
• Continually work with clients to ensure solutions achieve their goals and drive measurable value over time.

• Define requirements that translate use cases into actionable solution configurations based on FactualIQ’s engine and architecture, including tools, agents, and workflows.
• Incorporate user permissioning, data security, data confidentiality, and process auditability into solution designs to ensure transparency and enterprise-level compliance.
• Test and validate configured solutions against client requirements, ensuring quality assurance standards are met before deployment to production environments.
• Ensure solutions meet enterprise standards for reliability, performance, monitoring, and operational readiness at scale.

• Collaborate with data science and engineering teams to align requirements with platform capabilities, feature roadmaps, and implementation standards.
• Coordinate release planning and delivery, ensuring client alignment on timelines, dependencies, and expectations.
• Capture and document solution patterns, client playbooks, and lessons learned to build FactualIQ’s reusable knowledge base for future engagements.
• Provide structured feedback from client engagements to product and platform teams to inform roadmap priorities and capability gaps.
• Support post-deployment client enablement including onboarding, training, and operational handoff to ensure sustained adoption.

• Bachelor’s or higher degree in Information Systems, Computer Science, Engineering, Business, or related field (or equivalent practical experience).
• 5+ years of experience in software product management, solutions engineering, consulting, or technical client-facing roles, with demonstrated ownership of client engagements from discovery through delivery.
• Experience with AI-powered workflows and familiarity with multi-agent architectures, RAG pipelines, or model orchestration, including understanding of how these components integrate into enterprise decision-making systems.
• Demonstrated experience translating business workflows into product requirements, configuration specifications, and implementation plans.
• Hands‑on experience with AI/ML technologies including ML models, LLMs, RAG, and agentic systems, with familiarity with data pipelines and API-based integrations.
• Experience managing delivery timelines, cross-functional coordination, and stakeholder alignment across technical and business teams.
• Experience working in enterprise environments with awareness of complex stakeholder structures, governance…