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Forward Deployed Engineer (Applied AI)

$150K - $200K Remote Mid Posted September 14, 2026

Role Description

About The Role

We’re looking for a Forward Deployed Engineer (Applied AI) to build and deploy production-grade Conversational AI and Agentic AI solutions for enterprise customers.

What you’ll work on:

  • Build and deploy AI agents, conversational applications, and multi-agent workflows
  • Develop AI solutions using Python, GCP, APIs, RAG, and cloud technologies
  • Integrate AI systems with enterprise applications, data, and infrastructure
  • Build evaluation, monitoring, and observability solutions for AI agents
  • Work directly with customers and engineering teams to deliver high-impact AI solutions

What we’re looking for:

  • 5+ years of software development experience, preferably with Python
  • Hands-on experience with AI/ML and cloud architecture
  • Experience with GCP, Terraform, APIs, and enterprise integrations
  • Experience with Conversational AI / Dialogflow CX / Gemini / Contact Center AI
  • Strong troubleshooting and customer-facing engineering skills
  • Willingness to travel up to 50%

Interested? Apply Directly or You can contact [email protected]

Pay: $150,000.00 - $200,000.00 per year

Work Location: Hybrid remote in Texas City, TX 77592

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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