AI Strategist - US

Factify

About The Position

We're building Governed Truth Infrastructure for agentic AI in regulated industries - banking and insurance first - through a three-function architecture: Seal, Enforce, Prove. Two patents are already pending on the core architecture, on top of the registered patents already backing our technology. Design partners are live in production - real logos, real ARR targets. And we're building it for the people actually shipping this future: the developers, AI engineers, forward-deployed engineers, and AI strategists building and governing agents that do real work for their organizations and their clients. The FDE is now the fastest-growing role in tech - postings up 700%+ year over year (Indeed · Live Data Technologies, 2026). They all need a platform they can trust. That's what we're building.

Requirements

5+ years in product management, solutions engineering, technical consulting, technical program management, or another customer-facing technical role.
Experience taking complex software, data, machine-learning, or AI initiatives from concept through production and adoption.
Strong applied AI fluency, including familiarity with LLMs, agents, retrieval, tool use, prompt and context engineering, evaluations, and human-in-the-loop workflows.
A first-principles approach to turning ambiguous problems into practical, applicable solutions.
Strong product and systems judgment.
The ability to connect technical decisions to customer and business outcomes.
Excellent communication skills across technical and non-technical audiences.
High ownership, attention to detail, and follow-through.
Comfort operating in a fast-moving environment with evolving priorities.
Excellent written and spoken English.

Nice To Haves

Experience using Python, SQL, APIs, or modern AI tools to prototype and validate ideas.
Experience with workflow automation and orchestration tools (e.g., UiPath, n8n, Make, Power Automate, or Zapier)
Experience in financial services, insurance, or another regulated industry.
Familiarity with policy, compliance, risk, or other rules-driven workflows.
Experience working with enterprise requirements such as security, privacy, data governance, and system integrations.
A degree in computer science, data science, engineering, or another relevant technical or quantitative field, or equivalent hands-on experience.

Responsibilities

Develop a deep understanding of customer workflows, requirements, constraints, and goals.
Identify and prioritize high-value opportunities for applying AI.
Translate ambiguous business needs into clear solution plans, requirements, and success criteria.
Design and validate solution concepts through prototypes, demonstrations, and structured evaluations.
Define prompt, context, workflow, and evaluation approaches for AI-powered solutions.
Coordinate stakeholders and maintain alignment throughout implementation.
Guide trade-offs across speed, quality, reliability, scalability, governance, and customer impact.
Identify and resolve risks or blockers that could affect successful delivery.
Measure solution performance, adoption, and business value.
Turn recurring customer needs and implementation lessons into reusable capabilities and best practices.