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Senior Manager, AI Engineering & Product

Triune Infomatics

  • San Jose, CA
  • 1 day ago

    Highlights

    Must Have: Applied AI, LLM Systems & Inference Optimization, AI Agents & Agentic Frameworks, Distributed AI Infrastructure, AI Platform Architecture, Engineering & People Leadership. Overview: Senior hybrid IC and people leadership role bridging AI systems architecture, agentic AI, and cross-functional product execution.

    Numbers & Facts

    LocationSan Jose, CA

    Description

    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, GCP
    • 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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