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Dealops - Forward Deployed Strategist

$140K - $180K San Francisco, CA, US Mid Posted October 11, 2026

Role Description

Dealops: AI deal-pricing and revenue infrastructure for B2B (Airwallex, Plaid, Harvey, LangChain, Clay). 12 people, $7M from General Catalyst and Pear VC, SF.

Comp: $140K-$180K + 0.05%-0.15% equity. Location: on-site San Francisco. Visa: H1B transfer only.

Responsibilities

  • Design and run pilots, AI implementations and trainings to onboard customers
  • Own customer outcomes; drive adoption and expansion in key accounts
  • Work with Heads of Pricing, RevOps and Product at AI/fintech companies
  • Codify deployment best practices into product roadmap and GTM
  • Lead strategic projects turning user insights into product/business bets; scale repeatable patterns

Source: https://www.paraform.com/share/dealops/cmmbd894e00030clar0dz49cj

  • 3+ yrs across IB/elite consulting AND startup bizops/strategy (or startup bizops/deployment with end-to-end delivery)
  • Comfortable with senior customer leaders
  • Bonus: B2B pricing, GTM tools, AI agents
  • On-site SF; H1B transfer only

About Forward Deployed Engineering

Forward Deployed Engineers are embedded directly with customers to build custom solutions, integrate products into existing infrastructure, and bridge the gap between product engineering and customer success. The role combines deep technical skills with the ability to operate in client environments and translate business requirements into working software.

Originally pioneered by Palantir, the FDE model has spread across AI, enterprise SaaS, and cloud infrastructure companies. FDEs write production code, architect integrations, train customer teams, and feed product insights back to the core engineering organization. At companies like OpenAI, Salesforce, and Databricks, FDE teams are treated as elite engineering units that can ship custom solutions in days rather than quarters.

Typical FDE stack: Python, TypeScript, SQL, REST/GraphQL APIs, cloud platforms (AWS/GCP/Azure), and increasingly LLM APIs and AI orchestration frameworks. Strong communication and the ability to context-switch between technical and business conversations are as important as coding ability.

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