Forward Deployed AI Engineer

About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. 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 c [... source excerpt omitted ...] ers 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, [... source excerpt omitted ...] ment 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 autonomousl