Role Description
San Francisco, CA · On-site · Full-time
Compensation: $130,000–$170,000 + competitive equity
About the Company
We're an early-stage, venture-backed startup building the real-time data infrastructure that lets AI agents access live information from across the web. Our APIs and datasets power use cases from pipeline building and prioritization to sales/marketing automation and deal sourcing. With 150+ enterprise customers, $10M+ ARR, profitability, and 10x growth in 2025, we're scaling fast while staying disciplined.
Founded 2023 · 11–50 people · Industry: AI Tools
The Role
We're hiring a Customer Engineer to own customer success while actively building the automation that reduces manual customer touchpoints over time. This is a hybrid technical and relationship-driven role: you'll hop on calls when needed, but you'll be equally focused on building automated responses and workflows that scale support without scaling headcount. Prior customer success experience is not required — this is as much a builder's seat as a support seat.
What you'll be doing
- Own day-to-day customer success and support, including scheduling and running calls when necessary
- Build automations that reduce manual response volume over time
- Continuously improve how customer interactions are handled, balancing personal touch with scalable systems
- Identify patterns in customer needs and translate them into automated or systematized solutions
- Represent the voice of the customer back into the product and engineering teams
Tech stack: API integration and automation/workflow tooling.
Requirements
- 0-3 years, early-career welcome
- Genuine technical aptitude required
- Builder mindset: automation over manual process
- Personable, improvement-oriented
- SF 5 days in-person
- No prior CS experience required
Green Flags
- Software engineering background with genuine interest in moving into a more customer-facing role
- Demonstrated technical aptitude through side projects, coursework, or prior automation work
- Personable communicator who genuinely enjoys improving how customers experience the product
- High curiosity and hunger, even without direct customer success experience
- Comfortable building systems and processes rather than just executing manual tasks
Red Flags
- Pure support or ticket-handling background with no technical building interest
- Lacks genuine technical aptitude or curiosity about automation
- Passive approach to customer interactions rather than a builder's mindset
- Cannot work SF in-person 5 days a week
Why Join
- Build category-defining data infrastructure for the AI-agent era
- Rare traction for the stage: 150+ enterprise customers, $10M+ ARR, profitable, 10x growth in 2025
- A builder's seat with high autonomy and direct product influence early in your career
- Early-career friendly with a high ceiling — technical aptitude and hunger matter more than a CS resume
Details
- Location: San Francisco, CA
- Work policy: On-site, 5 days a week
- Compensation: $130,000–$170,000 + equity
- Visa sponsorship: None available
- Employment type: Full-time
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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