Forward Deployed Engineer
Forward Deployed Engineer who partners with customers to design, implement, and deploy production AI systems and workflows. Requires strong Python experience, customer-facing technical roles, and familiarity with AI/ML infrastructure and deployment.
About the job
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
Skills
Python, Docker, Kubernetes, Ai/Ml Pipelines, Model Serving Systems, Distributed Inference Workloads, vLLM, TensorRT, Ray, LangGraph, Vector Databases, Workflow Orchestration Systems, Inference Optimization, Gpu-Accelerated Workloads
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