Staff Forward Deployed AI Engineer

Confirmed live in the last 24 hours

Turing

Compensation

salary range: 180 - 230K

New York, New York, United States; San Francisco, California, United States

On-site

Posted March 26, 2026

Job Description

About Turing

Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises looking to deploy advanced AI systems. Turing accelerates frontier research with high-quality data, specialized talent, and training pipelines that advance thinking, reasoning, coding, multimodality, and STEM. For enterprises, Turing builds proprietary intelligence systems that integrate AI into mission-critical workflows, unlock transformative outcomes, and drive lasting competitive advantage.

Recognized by Forbes, The Information, and Fast Company among the world’s top innovators, Turing’s leadership team includes AI technologists from Meta, Google, Microsoft, Apple, Amazon, McKinsey, Bain, Stanford, Caltech, and MIT. Learn more at www.turing.com

About the Role

We’re seeking a highly skilled and motivated Forward Deployed Engineer (FDE) to work at the cutting edge of Generative AI deployments. In this role, you’ll partner directly with customers to design, build, and deploy intelligent applications using Python, Langchain/LangGraph, and large language models. You’ll bridge engineering excellence with customer empathy to solve high-impact real-world problems.

This is a hands-on engineering role embedded within customer projects—ideal for engineers who enjoy ownership, love solving hard problems, and thrive in dynamic, technical environments.

Key Responsibilities

Lead the end-to-end deployment of GenAI applications for customers—from discovery to delivery.
Architect and implement robust, scalable solutions using Python, Langchain/LangGraph, and LLM frameworks.
Act as a trusted technical advisor to customers, understanding their needs and crafting tailored AI solutions.
Collaborate closely with product, ML, and engineering teams to influence roadmap and core platform capabilities.
Write clean, maintainable code and build reusable modules to streamline future deployments.
Operate across cloud platforms (AWS, Azure, GCP) to ensure secure, performant infrastructure.
Continuously improve deployment tools, pipelines, and methodologies to reduce time-to-value.

Required Qualifications

5–8+ years of experience in software engineering or solutions engineering, ideally in a customer-facing capacity.
Proven expertise in Python, Langchain, LangGraph, and SQL.
Deep experience with engineering architecture, including APIs, microservices, and event-driven systems.
Demonstrated success in designing and deploying GenAI applications into production environments.
Strong proficiency with cloud services such as AWS, GCP, and/or Azure.
Excellent communication skills, with the ability to translate technical complexity to customer-facing narratives.
Comfortable working autonomously and managing multiple deployment tracks in parallel.

Preferred Qualifications

Familiarity with CI/CD, infrastructure-as-code (Terraform, Pulumi), and container orchestration (Docker, Kubernetes).
Background in LLM fine-tuning, retrieval-augmented generation (RAG), or AI/ML operations.
Previous experience in a startup, consulting, or fast-paced customer-obsessed environment.