AI Deployment Strategist
Posted today
pigmentBrooklyn (NY)
Data ScientistsComputer Systems Design Services
SENIORITY
Lead
About the role
Overview
As AI Deployment Strategist, you design, build, and deploy AI-powered planning solutions for key customers using Pigment. You will bridge engineering, data, and business problems to translate needs into scalable models and agent-based workflows. You influence how customers transform their planning processes and feed insights back to product and engineering. You collaborate with cross-functional teams to drive adoption and value realization. This role offers meaningful impact at scale within a fast-growing SaaS company.
Responsibilities Design, build, and deploy AI-powered Pigment solutions for strategic customers Translate complex problems into scalable Pigment models with AI agents and advanced logic Create custom AI agents aligned to customer workflows Lead end-to-end Pigment implementation for key accounts Partner with stakeholders to rethink processes and drive AI adoption Act as trusted advisor on best practices and scalable deployment patterns Prototype new AI use cases and iterate on agent-based planning Collaborate with Customer Success, Solutions Architects, and Product to capture requirements and feedback Train users on Pigment features and modeling best practices
Key requirements Engineering or computer science degree 2–5 years in a technical, client-facing, or implementation role Strong analytical and problem-solving skills in data modeling, analytics, or business logic design Knowledge of AI/ML concepts and data workflows Proficiency with formulas, logic, and structured modeling Programming experience (Python, SQL, or similar)Familiarity with SaaS platforms, APIs, data pipelines, and system integration Ability to manage multiple stakeholders and projects in fast-paced environments Excellent communication and stakeholder management Collaborative and consultative mindset Problem-solving and adaptability Formulas, logic, structured modelingAI / ML concepts and applied data workflows Python or SQL programming
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