Forward Deployed Engineer (FDE)

Requirements

• Ship Production Code: Design, build, and deploy custom integrations, APIs, and data pipelines directly within client environments.
  
• Own Client Architecture: Lead technical discovery, map out complex system architectures, and ensure seamless integration with client infrastructure.
  
• Scale AI Solutions: Implement practical AI workloads, including Large Language Model (LLMs) integrations, fine-tuning pipelines, and Retrieval-Augmented Generation (RAG) frameworks.
  
• Drive Product Roadmap: Act as the ultimate feedback loop. Identify recurring client pain points and collaborate with core R&D teams to turn custom client fixes into scalable platform features.
  
• Manage Technical Stakeholders: Serve as the trusted technical advisor to client CTOs, engineering leads, and business executives.
  

• Education: Bachelor’s degree in Computer Science, engineering, math, or equivalent practical experience.
  
•  Engineering Power: 3+ years of professional software development experience in languages like Python, Go, Java, or TypeScript.
  
• Systems & Data: Strong proficiency in SQL, data modeling, API design (REST/gRPC), and cloud infrastructure (AWS, GCP, or Azure).
  
• Communication: Exceptional ability to explain highly technical concepts plainly to non-technical business leaders.
  
• Mobility: Willingness to travel to client sites as needed (typically 25-50%).
  

• AI/ML Implementation: Hands-on experience building with LLM APIs, vector databases (e.g., Pinecone, Milvus), and orchestration frameworks (e.g., LangChain, Llama Index).
  
• Enterprise Savvy: Previous experience in a customer-facing engineering role (Solutions Architecture, Technical Consulting, or Forward Deployed Engineering).
  
• Infrastructure Fluency: Solid understanding of Docker, Kubernetes, CI/CD pipelines, and enterprise security frameworks.
  
• Adaptability: Proven track record of thriving in ambiguous environments and moving fast from 0 to 1.