Forward Deployed Engineer

Who We Are 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.   What We Are Looking For We are seeking an experienced  Forward Deployed Engineer  to partner directly with customers to architect, build, and deploy production AI systems and workflows on Lightning AI’s platform. In this role, you will own the customer journey from early exploration through production deployment, translating ambiguous business goals into reliable, observable systems with clear quality, latency, scalability, and cost outcomes. This role sits at the intersection of software engineering, research engineering, AI infrastructure, product thinking, and customer engagement. You’ll work closely with customer engineering teams as well as Lightning’s internal product and engineering organizations to deliver production-ready AI systems that help customers realize value quickly and scale with confidence. This is a hands-on engineering role that combines software development, AI infrastructure, technical customer engagement, and product thinking. Successful candidates will be  highly technical, customer-oriented builders who thrive in fast-moving environments and enjoy solving ambiguous, real-world AI systems problems. This role is based in one of our hubs (New York City, San Francisco, Seattle, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. What You'll Do Partner directly with customers to design, implement, and deploy end-to-end AI systems and workflows on Lightning’s platform Translate vague customer objectives into clear technical specifications, proof-of-concepts, and scalable production implementations Own customer technical engagements end-to-end, from early discovery and architecture through deployment, monitoring, and expansion Develop and maintain production-grade software systems and services using modern programming languages, with a strong preference for Python Build reliable, observable systems with strong attention to latency, throughput, quality, scalability, and cost efficiency in production environments Debug and optimize AI systems across inference infrastructure, model behavior, APIs, and distributed workloads to improve performance and reliability Work closely with customer engineering teams throughout the full lifecycle of AI deployments, including technical discovery, implementation, deployment, and scaling Collaborate cross-functionally with Lightning’s product and engineering teams to improve platform capabilities, influence roadmap priorities, and identify opportunities for reusable product improvements Navigate ambiguity with sound technical judgment, making thoughtful tradeoffs and selecting the right tools and approaches without introducing unnecessary complexity Demonstrate strong ownership and accountability in execution, with a commitment to delivering high-quality outcomes for both customers and internal teams What You’ll Need Required Qualifications 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 Nice-to-Haves Experience building, deploying, or optimizing large-scale AI/ML