Solutions Architect role for enterprise AI platforms (remote, United States). A partner company seeks a Solutions Architect with deep expertise in Generative AI and retrieval augmented generation (RAG) to lead the architecture of complex AI-driven solutions from concept through production. You will translate ambiguous business needs into scalable, secure, and resilient technical architectures and work with business leaders, product owners, engineering teams, and other architects across the United States. You will define AI reference architectures and enterprise standards, evaluate emerging technologies through proofs of concept, and provide technical mentorship to engineering teams. Responsibilities include owning end-to-end solution and platform architectures for large-scale distributed systems, designing for scalability, performance, resilience, security, and cost efficiency, and maintaining architecture documentation. Architect end-to-end AI workflows, design RAG pipelines, integrate AI capabilities into enterprise platforms via APIs and event-driven architectures, and assess tradeoffs between classical ML, LLM-based approaches, and non-AI solutions based on business needs. Requirements include a Bachelor's degree with 5+ years in an architecture role and hands-on AI architecture experience; strong Python and Java skills; cloud-native experience (AWS, Docker, Kubernetes); expertise with vector databases, data workflows, and LLM lifecycle considerations; knowledge of DevOps practices and API design; and experience in telematics or automotive industries is strongly preferr

Solutions Architect role for enterprise AI platforms (remote, United States). A partner company seeks a Solutions Architect with deep expertise in Generative AI and retrieval augmented generation (RAG) to lead the architecture of complex AI-driven solutions from concept through production. You will translate ambiguous business needs into scalable, secure, and resilient technical architectures and work with business leaders, product owners, engineering teams, and other architects across the United States. You will define AI reference architectures and enterprise standards, evaluate emerging technologies through proofs of concept, and provide technical mentorship to engineering teams. Responsibilities include owning end-to-end solution and platform architectures for large-scale distributed systems, designing for scalability, performance, resilience, security, and cost efficiency, and maintaining architecture documentation. Architect end-to-end AI workflows, design RAG pipelines, integrate AI capabilities into enterprise platforms via APIs and event-driven architectures, and assess tradeoffs between classical ML, LLM-based approaches, and non-AI solutions based on business needs. Requirements include a Bachelor's degree with 5+ years in an architecture role and hands-on AI architecture experience; strong Python and Java skills; cloud-native experience (AWS, Docker, Kubernetes); expertise with vector databases, data workflows, and LLM lifecycle considerations; knowledge of DevOps practices and API design; and experience in telematics or automotive industries is strongly preferr