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Forward Deployed Engineer
4MindsAI Inc.
Remote, USA
Full-time
Mid · 3+ years experience
Remote
USD 190000-225000 yearly / year
Discovered 1 weeks ago
PythonNode.jsTypeScriptWebRTCAPIsLLM pipelines
Free
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PythonNode.jsTypeScript
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PythonNode.jsTypeScriptWebRTCAPIsLLM pipelines
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Mission
4MINDS is an enterprise AI fine-tuning platform that transforms how organizations build and operate private, domain-specific AI. Unlike static systems, 4MINDS’ AI platform learns continuously from live data in real time and can be deployed on-prem or your cloud provider.
Our patented technologies scale existing engineering teams and empower new AI teams, enabling rapid AI deployment, adaptation, and ROI. Through 4MINDS’ automated data pipeline and proprietary knowledge graph, enterprises can connect all their data sources, including Microsoft, Databricks, AWS and Google, creating adaptive AI that surpasses the capabilities of conventional RAG-based systems.
Role Overview
As a Forward Deployed Engineer (FDE), you’ll operate at the intersection of engineering, AI, and live customer systems. You’ll work directly with enterprise clients to deploy, debug, and optimize 4MINDS LLM training platform.
This is a hands-on, field-facing engineering role. You’ll move between writing code, diagnosing live issues, building integrations, tuning models, and translating operational insights into core product improvements.
Reporting to the VP of Solutions Engineering, you'll make an impact for us and our customers by solving hard, messy, high-stakes problems where AI meets real operations.
Key Responsibilities
Partner directly with customers, from presales through onboarding and production, to ensure the 4Minds platform delivers new models for our clients.
Debug, tune, and optimize real-time LLM development pipelines for clients.
Build and maintain lightweight integrations, automations, and scripts connecting customer systems (TMS, CRMs, APIs) to our AI stack.
Work closely with core engineering and product teams to reproduce, isolate, and resolve field issues rapidly.
Develop deployment playbooks and reusable frameworks that make future rollouts faster and more reliable.
Surface insights and edge cases from customer operations to inform model tuning, UX design, and roadmap priorities.
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