Senior Manager, AI Engineering & Product

Role: Senior Manager, AI Engineering & Product

Location: San Jose, CA (Hybrid)

Duration: 3+ months

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  Overview:Senior hybrid IC and people leadership role bridging AI systems architecture, agentic AI, and cross-functional product executi
• onOperating level: IC10 / L7 or equivalent (Client, Google, Amazon, or high-growth AI startup calibr
• e)Expected to own roadmap, stakeholder alignment, and end-to-end delivery independent

ly
Must Have: Applied AI, LLM Systems & Inference Optimization, AI Agents & Agentic Frameworks, Distributed AI Infrastructure, AI Platform Architecture, Engineering & People Leaders

• hip
  Key Responsibilities:Build and scale AI deployment platforms focused on inference speed, latency reduction, and model accelera
• tionArchitect Client software libraries and tooling to push LLM inference and training optimiza
• tionDesign and lead multi-agent engineering systems including orchestration, parallelism, and tool u
• sagePrototype and incubate R&D innovations with potential patent v
• alueDrive cross-functional alignment and secure R&D budget from senior leader
• shipLead engineering teams with full autonomy across roadmap, staffing, and deli

• very
  Required Qualifications:15+ years in engineering, with 8 to 9 years in appli
• ed AIGroup Manager or Director level experience at a large tech company or high-growth AI st
• artupDeep hands-on expertise in LLM systems: transformers, inference optimization, quantization, KV cache, distributed training (PyTorch FSDP, PEFT/
• LoRA)Production-grade experience with AI Agents and agentic frameworks (Claude Code, Agent SDK, or equiva
• lent)Infrastructure at scale: Kubernetes, Kafka, Spark, multi-tenant SaaS, AWS
• , GCPProven record of building AI platforms from zero to enterprise production (F500 clients prefe
• rred)Experience with vector databases, synthetic data pipelines, RAG, Chain of Th

• ought
  Nice to Have:Published author or recognized thought leader in
• AI/MLStartup founding or enterprise incubation expe
• rienceGPU hardware ecosystem familiarity: CXL, NVMe, PCIe-level AI optimi
• zationStanford GSB or equivalent advanced edu

cation