Job Overview

As a Forward Deployed Engineer, you will play a key role in deploying AI systems for real-world customer environments. Customer Collaboration: Work directly with clients to understand workflows and translate needs into technical solutions. AI System Deployment: Design and implement agentic workflows using LLMs for task execution. Technical Expertise: 5+ years in ML (PyTorch, TensorFlow); 2+ years with LLMs (Hugging Face, OpenAI). Proven Experience: Building scalable AI systems, integrat...

Responsibilities

As a Forward Deployed Engineer, you’ll play a critical role in bringing advanced AI systems to life for customers. This is a deeply hands-on and highly collaborative role — you’ll work directly with client teams to understand their workflows, design solutions, and deploy production-grade AI systems in real environments. Your work will bridge technical execution with thoughtful communication and fast iteration, ensuring each deployment drives meaningful product impact.

• Partner directly with customers to understand their use cases, identify pain points, and translate needs into actionable technical solutions.
• Design and implement agentic workflows powered by LLMs for real-world task execution.
• Build customization layers tailored to organization-specific logic and deployment requirements.
• Deploy and iterate on LLM-powered pipelines with evaluation and feedback loops in production environments.
• Develop voice-based and message-based agents that drive engagement and adoption.
• Architect AI pipelines (RAG, prompt engineering, evaluation) and ensure reliable integration into complex infrastructures.
• Collaborate closely with product and engineering teams to bring field feedback directly into the product roadmap.
• Communicate clearly with both technical and non-technical stakeholders to align on goals and deliver solutions quickly.

Qualifications

Machine Learning Expertise

• 5+ years of experience in ML (PyTorch, TensorFlow).
• 2+ years of hands-on experience working with LLMs (Hugging Face, OpenAI, Anthropic).

AI System Development

• Proven experience building and deploying production AI systems, including RAG and vector search.
• Strong knowledge of prompt engineering, AI safety, and content filtering best practices.
• Comfort architecting scalable infrastructure that integrates into complex environments.

Customer Engagement & Communication

• Experience working directly with customers to deploy and iterate on technical solutions in real environments.
• Excellent communication skills with the ability to explain complex concepts clearly to both technical and non-technical stakeholders.
• Proven ability to gather feedback, shape product direction, and collaborate effectively with cross-functional teams.

Technical Proficiency

• Familiarity with Rails is a plus, but not required — strong candidates can ramp up quickly.
• Experience with REST APIs, PostgreSQL, ActiveRecord, and RSpec.
• Understanding of frameworks like LangChain or LlamaIndex, or the ability to learn them rapidly.

Builder Mindset

• Thrives in ambiguity, learns quickly, and iterates fast in lean environments.
• Excited to work in a small, high-impact team where communication and ownership are key.

Ideal Candidate

Ideal Candidate Profile

• Innovative Builder — Designs and deploys sophisticated AI workflows that solve complex, real-world enterprise challenges.
• Forward Deployed Mindset — Thrives on working directly with customers, gathering feedback, and iterating rapidly to solve problems in the field.
• Product-Minded Communicator — Excels at collaborating with users, clients, and cross-functional teams to shape solutions and drive adoption.
• Technically Excellent — Brings strong expertise in Rails (REST APIs, PostgreSQL, ActiveRecord, RSpec) and hands-on experience deploying scalable AI systems using modern frameworks and infrastructure.
• Collaborative and Fast-Moving — Thrives in ambiguity, learns new frameworks (LangChain, LlamaIndex, etc.) quickly, and delivers results at startup speed. Works seamlessly with founders, engineers, and product teams to iterate rapidly.