Forward Deployed Engineer

DAFY ONLINE operates “Get Driver,” an on-demand chauffeur service that provides convenient, reliable drivers anytime and anywhere. The service focuses on delivering a first-class travel experience, making it easy for customers to book professional drivers via their mobile devices. By combining technology with high-quality service standards, DAFY ONLINE aims to enhance personal and business travel. The company values innovation, customer satisfaction, and seamless digital experiences for its users.
About the Role
We are looking for a Junior Forward Deployed Engineer (FDE) who thinks in embeddings, understands agentic workflows, and builds with AI as much as they build for it.
As a Forward Deployed Engineer, you are the bridge between our core product and our enterprise customers. You won't just be writing software in a vacuum; you will be directly engaged with clients, understanding their unique data architectures, and writing the custom integrations required to make our AI platform work perfectly in their environment.
You will be part engineer, part consultant, and a full-time problem solver.
What You’ll Do
Deploy & Integrate: Write the "glue code" (primarily in Python or TypeScript) to connect complex client data pipelines, APIs, and legacy systems to our core AI platform.
Build Custom AI Workflows: Design and implement Retrieval-Augmented Generation (RAG) pipelines, configure AI agents, and optimize prompts for highly specific enterprise use cases.
Customer Collaboration: Work directly with client stakeholders (from technical leads to business managers) to scope requirements, demonstrate progress, and troubleshoot deployment roadblocks.
Evaluate & Iterate: Build custom evals to measure LLM performance on client-specific tasks, ensuring our models don't just generate text, but deliver accurate, reliable business value.
Product Feedback Loop: Act as the technical voice of the customer. Identify patterns in client needs and relay them to the core engineering team to shape the product roadmap.
The "AI-Native" Expectation
You code with copilots: You are a fluent power-user of AI coding assistants (like Cursor, GitHub Copilot, or Claude) to accelerate your velocity. You know how to prompt the IDE as well as the API.
You understand the limits: You intuitively grasp the difference between a deterministic function and a probabilistic LLM output, and you know how to engineer fallbacks, guardrails, and validation steps.
You keep pace: You actively follow the AI ecosystem (new model releases, context window expansions, agentic frameworks) and apply new paradigms to your daily work.
What We’re Looking For
Experience: 1–2 years of software engineering experience (rigorous internships or impressive personal AI projects count) with strong proficiency in Python and/or TypeScript.
AI Tooling: Hands-on experience building applications using foundation model APIs (OpenAI, Anthropic, Gemini, etc.).
Data Systems: Familiarity with modern data infrastructure, including REST APIs, SQL, and Vector Databases (e.g., Pinecone, Weaviate, Qdrant).
Communication: Exceptional interpersonal skills. You can explain complex AI concepts (like vector search or token limits) to non-technical stakeholders without losing them.
Scrappiness: A bias for action. You are comfortable diving into poorly documented client systems, debugging on the fly, and finding creative workarounds.
Bonus Points
Experience with LLM orchestration and evaluation frameworks (e.g., LangChain, LlamaIndex, DSPy).
Prior experience in a customer-facing technical role (Sales Engineering, Solutions Architecture, or Tech Consulting).
Basic frontend skills (React/Next.js) to quickly spin up internal tools or proof-of-concept UIs for clients.

Work arrangement
Hybrid