Deployment Strategist

Recruiting From Scratch • San Francisco, NY

13h • Hybrid

About The Position

The Deployment Strategist leads enterprise deployments of an AI-native mortgage servicing software platform for large financial institutions. The role works directly with customers to understand their operations, workflows, data, and legacy systems, then translates business needs into platform configurations, implementation plans, and scalable software-driven workflows. Strategists own deployments from discovery through implementation, adoption, and ongoing improvement, with responsibility for measurable customer outcomes.

The role sits at the intersection of strategy, operations, technology, and customer delivery. It partners closely with Product, Engineering, and customer stakeholders to investigate operational problems, resolve implementation challenges, and ensure technical solutions address underlying business needs. The Strategist also builds repeatable deployment playbooks, tooling, and processes, using AI tools, coding agents, and data analysis to improve execution and scale the deployment function.

The position is hybrid, based in the New York City or San Francisco office. The team generally works in the office Tuesday through Thursday, with a minimum of two in-office days per week. Domestic travel is required for customer deployments, estimated at approximately 10–20%.

Requirements

• 3–6 years of professional experience.
• Experience at a top strategy consulting firm, top investment bank, or top private equity firm or hedge fund; the posting identifies this as a dealbreaker requirement.
• An undergraduate degree from a top 20 university or recognized international equivalent; examples include Oxford, Cambridge, LSE, and Waterloo.
• Demonstrated active use of AI tools and coding agents in current workflows; practical AI fluency is described as non-negotiable.
• Strong first-principles thinking, structured problem-solving, quantitative and analytical reasoning, and ability to identify root causes.
• Ability to solve complex, ambiguous problems and make sound decisions with incomplete information.
• High agency, bias toward action, and demonstrated ownership of projects and measurable outcomes.
• Ability to build processes, tooling, playbooks, or operating models from scratch and execute without relying on existing templates.
• Ability to work under pressure, manage competing priorities and stakeholders, and deliver under demanding timelines.
• Strong written and verbal communication and ability to explain complex ideas clearly.
• Ability to work with enterprise customers and senior stakeholders and translate between business requirements and technical implementation.
• Ability to collaborate effectively with software engineers, Product, Engineering, and operational teams.
• Comfort working with data, investigating operational problems, validating assumptions, and learning new technical tools quickly.
• Strong professional stability; the posting notes that multiple tenures of less than one year are a concern.

Nice To Haves

• Experience at Scale AI or a similar high-growth AI-native startup.
• Experience deploying enterprise software or implementing complex technology solutions.
• Experience in mortgage servicing, financial services, or regulated enterprise environments.
• Familiarity with SQL, Python, data analysis, and data warehousing.
• Experience building operational playbooks, internal tooling, or scalable implementation processes.
• Experience using AI coding agents to automate workflows or accelerate execution.
• Experience managing enterprise implementations or complex cross-functional projects.
• Experience in roles combining strategy, operations, and technology.
• Promotions and increasing responsibility within the same organization are strong positive signals.

Responsibilities

• Lead enterprise mortgage servicing platform deployments from initial discovery through implementation, adoption, and ongoing improvement.
• Understand customers’ existing operations, workflows, systems, and operational challenges.
• Translate business requirements into platform configurations and implementation plans.
• Coordinate deployment activities and take ownership of measurable customer outcomes.
• Observe customer workflows on-site, analyze processes, data, and legacy systems, and identify inefficiencies and undocumented requirements.
• Partner with Product and Engineering to translate operational requirements into scalable software solutions.
• Use data analysis and technical tools to investigate problems, validate assumptions, and identify implementation constraints.
• Apply first-principles reasoning to ambiguous problems, identify root causes, and make decisions with incomplete information.
• Develop repeatable playbooks, implementation frameworks, tooling, and standardized processes for future deployments.
• Use AI tools and coding agents to automate repetitive work and improve deployment efficiency and consistency.
• Drive customer adoption, monitor implementation progress, resolve obstacles, and evaluate business outcomes.
• Communicate deployment progress, risks, decisions, and customer feedback across Engineering, Product, and customer-facing teams.
• Align internal stakeholders on priorities and implementation plans, and contribute to continuous improvement.

Benefits

• Competitive equity through RSUs or stock options, depending on eligibility and offer structure; subject to a vesting schedule with a one-year cliff followed by monthly vesting.
• Sign-on bonuses may be available.
• Relocation assistance of up to $10,000, subject to eligibility.
• Lunch and dinner provided on in-office days.
• Dog-friendly New York City office.
• Hybrid working arrangements in New York City or San Francisco.
• High ownership and direct exposure to enterprise customers, Engineering, and Product strategy.
• AI-native work environment with coding agents and custom AI workflows integrated into daily operations.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level