Forward Deployed Engineer

Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.

Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.

We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.

• →Strong software engineering experience building and maintaining production systems in one or more general-purpose programming languages, with Python strongly preferred
• →Experience working directly with customers in highly technical environments, such as Forward Deployed Engineering, Solutions Engineering, Applied AI Engineering, Technical Product Engineering, or related roles
• →Familiarity with AI/ML pipelines and the lifecycle of model development, evaluation, deployment, and monitoring
• →Experience deploying and operating production AI/ML systems in cloud or distributed environments
• →Familiarity with modern AI infrastructure and tooling such as Docker, Kubernetes, APIs, model serving systems, or distributed inference workloads
• →Strong communication and collaboration skills, especially when working through complex technical topics with customers, engineers, and cross-functional stakeholders
• →Ability to translate business needs into technical solutions and drive projects from initial concept through production delivery
• →Ability to execute effectively in ambiguous, fast-moving, high-growth environments
• →Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field

• Experience building, deploying, or optimizing large-scale AI/ML systems in production environments
• Experience with modern AI stacks and tooling such as vLLM, TensorRT, Ray, LangGraph, vector databases, or workflow orchestration systems
• Familiarity with inference optimization, distributed systems, or GPU-accelerated workloads
• Startup experience or experience operating in highly cross-functional environments
• Track record of rapidly shipping proof-of-concepts and production systems while maintaining strong engineering quality
• Advanced degree (Master’s or PhD) in Computer Science, Engineering, Mathematics, AI, or a related technical field