Forward Deployed Engineer

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What the market looks like

Forward deployed engineering is a small but fast-growing category — we track a few hundred postings in the US in any given year, clustered at AI-native product companies selling into the enterprise. These roles are predominantly remote or travel-heavy hybrid, with base compensation generally in a $150K–$230K range plus meaningful variable upside. The strongest forward deployed engineers we place are unusually generalist — equally comfortable with data pipelines, model integration, and a customer call at 4pm on a Friday.

Job responsibilities

• Work directly with enterprise customers to design, implement, and deploy AI-enabled solutions on top of the platform

• Translate ambiguous customer requirements into concrete technical specifications and ship production integrations rapidly

• Serve as the primary technical point of contact throughout onboarding and early use

• Pair with customer data, engineering, and product teams in their environments — on-site or remote — to unblock adoption

• Capture patterns and gaps from the field and feed them back to product and engineering with signal, not just anecdote

• Troubleshoot complex data, integration, and modeling problems that sit outside the standard playbook

• Influence product direction based on what actually works (and doesn't) in real customer deployments

• Build shared assets — templates, integration patterns, evaluation suites — that accelerate the next rollout

Candidate requirements

• 5+ years of software, data, or ML engineering experience with strong generalist range

• Experience working directly with enterprise customers — solutions engineering, field engineering, or forward-deployed roles

• Strong Python and SQL, with comfort across multiple cloud environments

• Ability to move fast from ambiguous customer requests to shipped technical solutions

• Excellent written and verbal communication with both engineers and business stakeholders

• Willingness to travel when needed (typically 10–25%)