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Perplexity

AI Strategist, Financial Services

Hybrid · San Francisco, CA

This hybrid role accepts applicants from: United States.

Locations: San Francisco, CA · New York City, NY

Apply on the employer's siteOriginal listingJSON

PeopleSeek Talent does not submit applications. The button opens the employer's own page; this listing was verified 3 hours ago.

PayUSD 215,000 – 250,000 per year
Work arrangementHybrid
Who can applyPeople in United States
LevelNot stated
TypeFull time
Occupationfinancial broker
LanguageNot stated
Posted23 July 2026
Last verified3 hours ago
StatusActive

About the role

Perplexity is an AI-powered answer engine founded in December 2022 and growing rapidly as one of the world's leading AI platforms. Perplexity has raised over $1B in venture investment from some of the world's most visionary and successful leaders, including Elad Gil, Daniel Gross, Jeff Bezos, Accel, IVP, NEA, NVIDIA, Samsung, and many more. Our objective is to build accurate, trustworthy AI that powers decision-making for people and assistive AI wherever decisions are being made.

Throughout human history, change and innovation have always been driven by curious people. Today, curious people use Perplexity to answer more than 780 million queries every month—a number that's growing rapidly for one simple reason: everyone can be curious.

About the Role

Perplexity is building the AI platform for professional finance: Perplexity Computer, our agentic platform that navigates tools, completes multi-step workflows, and connects to the market data, filings, transcripts, and research that investment professionals already rely on, and our API Platform, which powers search, retrieval, and automation across structured and unstructured financial data.

At the center of this is our Applied AI / Forward Deployed motion: we work closely with buyside firms—hedge funds, private equity, and asset managers—to distill their core investment processes and embed them into bespoke solutions built on our platform. That means sitting with analysts and PMs to understand how they screen, diligence, monitor, and decide, then translating those workflows into custom skills, agents, and connector configurations that run inside their daily process—and feeding what we learn back into the product so it compounds across customers.

As an AI Strategist on our Applied AI team focused on financial services, you are the subject matter expert who makes this real for investment professionals. This is a commercial and sales engineering role: you will own strategic customer engagements end to end—leading discovery, defining what to build, demonstrating frontier capabilities against real investment workflows, and driving deployments from first conversation through production and expansion. You are part customer owner, part product strategist, part sales engineer—fluent in both the language of the deal team and the language of the platform.

Responsibilities

Own strategic financial-services engagements

  • Lead discovery with banks, PE firms, hedge funds, and asset managers: what matters to the investment team, what problems they are solving, and which workflows are worth automating

  • Define scope—what is the right thing to build—and own success metrics, pilot design, and commercial structure

  • Drive deployment and rollout across front-office teams, with real revenue responsibility alongside Sales

Be the demo and technical proof engine

  • Build and deliver compelling, workflow-specific demonstrations: screening, comps, diligence, earnings analysis, research synthesis, portfolio monitoring

  • Prototype workflows, skills, and connector configurations hands-on in Perplexity Computer and the API Platform to prove value in the customer's own use cases

  • Run pilots and evaluations that hold up to scrutiny from skeptical analysts and PMs

Bring domain judgment to the product

  • Translate how deal teams, research desks, and portfolio managers actually work into product, connector, and data-partnership priorities

  • Assess whether we have the right market data, filings, transcripts, and research integrations to serve each finance sub-vertical—and drive the roadmap where we do not

  • Codify repeatable engagement patterns: discovery templates, finance-specific reference workflows, demo libraries, and deployment playbooks

Operate as the commercial lead

  • Own senior relationships with investment professionals and technology leaders; move engagements through qualification, scoping, proposal, pricing, legal, and close

  • Create urgency, write crisp follow-ups, and know when to push and when to wait

Qualifications

  • 3+ years of direct experience in investment banking, private equity, hedge funds, equity research, or institutional asset management—you have built models, written memos, and lived the workflows you will now automate

  • 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

Nice-to-Haves

  • 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

If you're excited about this role, we encourage you to apply even if your experience doesn't match every qualification listed above.

Listed via Perplexity · first seen 22 October 2026 · last verified 28 October 2026

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