Mlops Engineer

Role: Senior Manager, AI Engineering & Product Location: San Jose, CA (Hybrid) Duration: 3+ months Overview: Senior hybrid IC and people leadership role bridging AI systems architecture, agentic AI, and cross-functional product execution Operating level: IC10 / L7 or equivalent (Client, Google, Amazon, or high-growth AI startup calibre) Expected to own roadmap, stakeholder alignment, and end-to-end delivery independently Must Have: Applied AI, LLM Systems & Inference Optimization, AI Agents & Agentic Frameworks, Distributed AI Infrastructure, AI Platform Architecture, Engineering & People Leadership Key Responsibilities:

• Build and scale AI deployment platforms focused on inference speed, latency reduction, and model acceleration
• Architect Client software libraries and tooling to push LLM inference and training optimization
• Design and lead multi-agent engineering systems including orchestration, parallelism, and tool usage
• Prototype and incubate R&D innovations with potential patent value
• Drive cross-functional alignment and secure R&D budget from senior leadership
• Lead engineering teams with full autonomy across roadmap, staffing, and delivery

Required Qualifications: 15+ years in engineering, with 8 to 9 years in applied AI Group Manager or Director level experience at a large tech company or high-growth AI startup Deep 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 equivalent) Infrastructure at scale: Kubernetes, Kafka, Spark, multi-tenant SaaS, AWS, Google Cloud Platform Proven record of building AI platforms from zero to enterprise production (F500 clients preferred) Experience with vector databases, synthetic data pipelines, RAG, Chain of Thought Nice to Have: Published author or recognized thought leader in AI/ML Startup founding or enterprise incubation experience GPU hardware ecosystem familiarity: CXL, NVMe, PCIe-level AI optimization Stanford GSB or equivalent advanced education

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