Forward Deployed Engineer

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 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

Benefits

• Comprehensive medical, dental and vision coverage (U.S.); Private medical and dental insurance (U.K.)
• Retirement and financial wellness support (U.S.); Pension contribution (U.K.)
• Generous paid time off, plus holidays
• Paid parental leave
• Professional development support
• Wellness and work-from-home stipends
• Flexible work environment