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CLERA

Forward Deployed Engineer (Founding Customer Engineer)

$140K - $185K San Francisco, CA, US Mid Posted July 21, 2026

Role Description

About the Role

This is a rare opportunity to be the first non-founder hire at a seed-stage B2B SaaS company building AI-powered autonomous demo and sales agents for go-to-market teams. You'll own every customer relationship end-to-end and build the playbook that scales the customer base from tens of customers to thousands.

You'll sit at the intersection of technical depth and customer empathy — coaching AI agents, automating workflows, and translating real customer conversations directly into product decisions alongside the founding team.

What You'll Do

  • Teach and coach AI agents on product positioning, buyer personas, pricing conversations, and sales tiers to improve their performance.
  • Own customer relationships end-to-end — from onboarding through ongoing success, demo improvement, and adoption.
  • Serve as the voice of the customer: mine conversation logs and feedback to surface patterns and inform the product roadmap.
  • Build automation workflows and systems (scripting, APIs, low-code/no-code tools) to scale the customer engineering function without proportional headcount growth.
  • Collaborate directly with the CTO to translate customer insights into shipped product features.
  • Define and document the repeatable playbook for customer onboarding, success, and expansion.

What We're Looking For

Required

  • 0–3 years of experience in a customer-facing technical role in SaaS (e.g., solutions engineer, customer engineer, technical account manager).
  • Strong written and verbal communication skills; demonstrated ability to lead product demos and customer onboarding sessions.
  • Hands-on experience building automation workflows to scale customer engineering tasks (scripting, REST APIs, or low-code/no-code platforms).
  • Ability to analyze customer feedback and conversation logs to identify meaningful patterns and translate them into actionable product improvements.
  • Experience coaching or configuring AI agents for sales contexts — defining personas, tiers, and pricing conversations.
  • Instinct to identify repetitive manual work and eliminate it through tooling or automation.
  • Must be authorized to work in the United States without visa sponsorship.
  • Must be able to work on-site in San Francisco, CA.

Nice to Have

  • Background in or exposure to GTM, sales engineering, or revenue operations at a high-growth B2B SaaS company.
  • Familiarity with interactive demo platforms, conversational AI, or sales automation tooling (e.g., companies like Walnut, Navattic, Storylane, Arcade, Demostack).
  • Experience working in a very early-stage (seed / pre-seed) environment where you've built processes from scratch.

Compensation & Benefits

  • Salary: $140,000 – $185,000 USD annually
  • Early-stage equity participation
  • Direct impact on company direction as the first non-founder hire

Location

  • On-site in San Francisco, CA (required)
  • Visa sponsorship is not available — candidates must be authorized to work in the US without sponsorship

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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