AI Systems ArchitectLocation: SFO, CA & San Leandro, CA (Hybrid)Duration: Contract for 12 + MonthsJob DescriptionWe are seeking an experienced AI Systems Architect to design, build, and scale high-performance distributed AI systems. The ideal candidate will have deep expertise in GenAI, LLMs, and cloud-native architectures, along with hands-on experience in building enterprise-scale AI/ML platforms and agent-based systems.Must-Have SkillsStrong experience in designing and implementing high-performance, large-scale distributed systemsProven experience in implementing and deploying AI/ML platforms at scaleExpertise in building agent-based architectures, evaluation frameworks, and prompt/context engineeringKnowledge of MCP (Model Context Protocol) serversHands-on experience in LLM inference optimization, including batching and caching strategiesStrong experience with Kubernetes and cloud infrastructure (AWS/Azure/GCP)Proficiency in at least one programming language (Python, Java, Go, etc.)Expertise in designing agent data stacks & retrieval systems, including:Vector databasesHybrid searchData freshness strategiesMemory systemsGraph reasoningBM25 and advanced retrieval techniquesKey ResponsibilitiesArchitect and deliver scalable, high-performance distributed systemsDesign and deploy AI/ML and GenAI platforms at enterprise scaleBuild and manage agent-based architectures, including:Prompt and context engineeringMCP serversEvaluation frameworksOptimize LLM inference pipelines for latency, throughput, and efficiencyDesign and implement agent data & retrieval systems (vector DBs, hybrid search, memory, graph-based reasoning)Lead Kubernetes-based, cloud-native deploymentsProvide technical leadership, architecture governance, and hands-on mentoring to engineering teamsNice to HaveExperience with RAG (Retrieval-Augmented Generation) frameworksFamiliarity with multi-agent systems and orchestration frameworksExposure to real-time data pipelines and streaming architectures