Client Solutions Analyst

Summary

FactualIQ is a company focused on enhancing enterprise decision-making through AI-enabled solutions. The Client Solutions Analyst role involves collaborating with clients to model decision processes and develop prototypes, while also managing client relationships and contributing to solution design and performance tracking.

Responsibilities

• Drive decision discovery with clients: document decision processes, constraints, data inputs, and objectives. Then build. Design and iterate LLM-based prototypes — including RAG workflows using tools like Claude Code, Python, and SQL. You’ll assess data quality and availability, structure retrieval, engineer and refine prompts, evaluate outputs, and iterate against real client data
• Translate decision requirements into conceptual solution designs, user stories, and measurable acceptance criteria. Support business QA and user acceptance testing at handoff. Track solution performance against defined success metrics through early adoption, providing structured analysis back to the client and the internal team
• Serve as the client-facing partner from kickoff through prototype delivery. Provide clear, honest progress updates, manage scope expectations, and surface blockers early. Collaborate with solutions engineers and practice leaders during production hardening. Capture solution patterns, decision models, and lessons learned to build FactualIQ’s delivery knowledge base and strengthen our operating model

Skills

• 2+ years delivering AI or analytics engagements at a consulting firm, technology implementation practice, or AI/ML professional services organization — with direct accountability for client outcomes, not just requirements capture
• Demonstrated ability to develop LLM or RAG-based prototypes independently, including prompt design, retrieval setup, and evaluation against real-world data
• Proficiency in Python, comfort querying and wrangling structured and semi-structured data as a routine part of the work
• Familiarity with enterprise AI tooling — Claude Code, OpenAI APIs, LangChain, vector databases, or equivalent
• Experience translating ambiguous business problems into clear functional requirements and measurable success criteria
• Direct client-facing experience in enterprise environments, including managing stakeholder communication and navigating complex organizational structures
• Strong written and verbal communication skills across both technical and executive audiences
• Background in management consulting, technology implementation, or an analytics-driven professional services organization, with experience owning client-facing delivery from kickoff through handoff
• Experience with structured and unstructured data across construction, architecture and engineering, real estate, affordable housing, financial services, healthcare, or other enterprise verticals
• Exposure to decision intelligence concepts such as decision modeling, confidence scoring, traceability from input data to recommendation
• Horizontal industry range with the ability to recognize cross-sector decision patterns and adapt delivery approaches

Qualifications

Must Haves

• 2+ years delivering AI or analytics engagements at a consulting firm, technology implementation practice, or AI/ML professional services organization — with direct accountability for client outcomes, not just requirements capture
• Demonstrated ability to develop LLM or RAG-based prototypes independently, including prompt design, retrieval setup, and evaluation against real-world data
• Proficiency in Python, comfort querying and wrangling structured and semi-structured data as a routine part of the work
• Familiarity with enterprise AI tooling — Claude Code, OpenAI APIs, LangChain, vector databases, or equivalent
• Experience translating ambiguous business problems into clear functional requirements and measurable success criteria
• Direct client-facing experience in enterprise environments, including managing stakeholder communication and navigating complex organizational structures
• Strong written and verbal communication skills across both technical and executive audiences

Nice to Haves

• Background in management consulting, technology implementation, or an analytics-driven professional services organization, with experience owning client-facing delivery from kickoff through handoff
• Experience with structured and unstructured data across construction, architecture and engineering, real estate, affordable housing, financial services, healthcare, or other enterprise verticals
• Exposure to decision intelligence concepts such as decision modeling, confidence scoring, traceability from input data to recommendation
• Horizontal industry range with the ability to recognize cross-sector decision patterns and adapt delivery approaches

Benefits

• This is a fully remote role.
• The team is established in Vancouver BC, Seattle, and Chicago, and expanding in Denver and Dallas.
• Travel Requirements: This role may require periodic travel within the United States and Canada based on client needs and project phases, typically less than 25% annually.