Forward Deployed Strategist

Varick Agents•San Francisco, CA

4d•$160,000 - $230,000•Onsite

About The Position

Varick's Forward Deployed Strategists are client-facing operators who embed with enterprise teams to understand operational workflows and guide engagements from initial discovery through an AI agent running in production. They work with stakeholders from C-suite executives to frontline operators, identify how work actually happens—including exceptions, workarounds, and cross-team handoffs—and turn findings into business cases and actionable briefs for engineers. The role is not software engineering, pure strategy, model research, or checklist-based implementation; strategists do not write production code or train and fine-tune models. Strategists collaborate closely with engineers on live deployments, scope agents, and use Varick's AI-native tools. They help clients define success measures and change how process owners work alongside agents, then support adoption and assess results. The role also involves developing Varick's playbooks, sharing client feedback with product and engineering teams, and finding opportunities to expand AI transformation across existing client departments. The position is based in San Francisco, with on-site work at Varick's Financial District office and 20–40% travel to client sites. The company describes a fast-moving startup environment with long hours and expected weekend work. Meaningful equity is offered.

Requirements

Track record of solving difficult, ambiguous problems for senior stakeholders and seeing the work through to results.
Strong executive communication and client presence; ability to tailor communication to different audiences and levels of detail.
Analytical rigor, including the ability to research and document findings, model a business, pressure-test numbers, and quickly learn unfamiliar industries and workflows.
Strong commercial judgment and understanding of value, buyers, and what constitutes a successful client engagement.
AI-curious and AI-fluent; uses AI tools regularly, follows developments in the field, and can articulate where agents are and are not useful.
Ability and desire to communicate with engineers about what to build, without needing to be an engineer.
Comfort working in an ambiguous, fast-paced startup environment with long hours and expected weekend work.
Based in San Francisco or willing to relocate; able to work on-site at the Financial District office and travel 20–40% to client sites.

Nice To Haves

Investment banking experience, ideally in IBD at a top-tier bank, in M&A, ECM, DCM, or leveraged finance.
Private equity investment-team experience as an analyst or associate at a top-tier fund.
Top-tier strategy consulting experience, especially with a digital, AI, or operations focus.
BizOps, Chief of Staff, or corporate strategy experience at a high-growth startup or mid-size technology company.
Deployment Strategist experience at a top-tier AI company.
Founder or early-employee experience at a startup that sold to enterprises.
Transformation or operations leadership experience in finance, operations, or strategy at a Fortune 500 company.
Evidence of a competitive mindset and strong performance, for example in sports, eSports, a previous career, or research.

Responsibilities

Embed with client teams across departments to map workflows step by step and system by system, including exceptions, workarounds, and cross-team handoffs.
Run rigorous discovery engagements, including stakeholder interviews, process mapping, hypothesis-driven analysis, and executive readouts.
Build business cases by sizing opportunities, modeling value, and prioritizing workflows for automation based on potential savings and value.
Translate ambiguous business problems into agent briefs with clear success criteria, guardrails, and definitions of done for engineers.
Co-create KPIs with clients, establish pre-launch baselines, and communicate post-deployment results and uplift.
Drive adoption by training client teams, observing users, and feeding observations into subsequent iterations.
Present findings, recommendations, and results to C-suite stakeholders and defend them under pressure.
Codify effective approaches into Varick's playbooks, frameworks, and toolkit, and share client feedback with product and engineering teams.
Develop relationships with existing clients to identify further AI transformation opportunities within and across departments.
Work alongside engineers on live deployments, scope agents, and use Varick's AI-native toolkit.