Draftwise
Deployment Strategist - New York
$150K–$190K
New York City, NY · Hybrid · Full-time · Posted Sep 15, 2026
- Experience
- 3+ years; relevant experience may be in deployment strategy, forward-deployed work, product discovery, solutions engineering, consulting, or another customer-facing technical role.
About the job
Embeds with law-firm customers to uncover high-value workflows, deliver measurable outcomes with Draftwise, and turn validated needs into reusable product capabilities.
What you'll do
- Observe customer work and map workflows, documents, data, systems, and constraints to identify where Draftwise can create value.
- Build and test prototypes, automations, and evaluations; translate findings into product requirements and drive them through delivery.
- Distinguish customer-specific requests from repeatable needs and help develop reusable capabilities, configurations, evaluations, and playbooks.
What they ask for
- 3+ years of experience in deployment strategy, forward-deployed work, product discovery, solutions engineering, consulting, or another customer-facing technical role owning outcomes in complex environments.
- Track record of taking ambiguous, high-stakes customer problems from discovery through product requirements to shipped solutions with material outcomes.
- Strong technical fluency and hands-on experience with modern AI tools, including querying data, working with APIs and data models, and building prototypes or automations.
- Strong communication, presentation, analytical judgment, and delivery skills; willingness to travel and spend meaningful time onsite.
Nice to have
- Familiarity with legal workflows, law-firm knowledge systems, document management systems, or complex professional-services environments.
- Experience practicing law or working in legal innovation, knowledge management, legal operations, or legal technology.
Pay
USD 150,000–190,000 (YEARLY) base salary
Tools
APIs, data models, AI coding tools, Microsoft Word
AI focus
Use Draftwise AI tools and customer data to test feasibility, build prototypes and evaluations, and identify workflows where AI can produce measurable value.
Model-written summary · the original posting is authoritative