AI Strategist, Financial Services
$215,000–$250,000 year
RemoteUnited States or San Francisco, California, United States
Job Summary
Lead discovery with banks, PE firms, hedge funds, and asset managers to define scope, success metrics, and commercial structures for bespoke AI solutions. Drive end-to-end deployments from first conversation through production, translating front-office workflows into custom skills, agents, and connector configurations. Build and deliver workflow-specific demonstrations for screening, diligence, and earnings analysis while running pilots that withstand scrutiny from skeptical analysts. Own senior relationships with investment professionals and technology leaders, moving engagements through qualification, scoping, proposal, pricing, legal, and close. Codify repeatable engagement patterns including discovery templates, reference workflows, and deployment playbooks to scale across customers.
Required Qualifications
- 3+ years of direct experience in investment banking, private equity, hedge funds, equity research, or institutional asset management
- 6+ years of total experience spanning finance and some combination of technical GTM, sales engineering, solutions architecture, AI product strategy, or applied AI with customer exposure
- Deep fluency in front-office workflows: screening, comps, diligence, earnings, research synthesis, portfolio construction and monitoring
- Strong intuition for AI products, agents, and workflows, with the ability to understand technical systems without needing every detail pre-digested
- Comfortable working shoulder-to-shoulder with Forward Deployed Engineers and technical teams: scoping builds together, pairing on prototypes, and translating customer requirements into engineering-ready specs
- Demonstrated ability to turn ambiguous customer problems into scoped, executable deployment plans with clear success metrics
- Strong commercial instincts and comfort operating with MDs, partners, PMs, CIOs, and CTOs
- Excellent written and verbal communication; able to write proposals, customer memos, technical scopes, and launch narratives
- High agency and low ego, with the ability to run multiple complex customer workstreams in parallel and make progress before the playbook exists
Desired Qualifications
- Hands-on experience building with agentic systems, tool-use workflows, MCP, or LLM APIs
- Working knowledge of institutional data platforms: FactSet, Bloomberg, S&P Capital IQ, PitchBook, Morningstar, or similar
- Experience selling or deploying technology into regulated financial institutions, including security and compliance review
- Founder or early-startup operating experience
- Strong network across buy-side and sell-side institutions
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