Job Title - Principal AI Architect
Location : Mountain View, CA
Must-Have Experience
∙ 12+ years of hands-on experience in AI/ML engineering and data science, with significant depth in production system delivery.
∙ Deep, working expertise in LLM application development: LangChain, LangGraph, tool-calling agents, RAG, prompt engineering, embedding pipelines, and hybrid retrieval.
∙ Proven track record architecting and shipping multi-agent systems, knowledge graph-powered retrieval (Neo4j or equivalent), and real-time inference APIs.
∙ Strong ML fundamentals: XGBoost, deep learning, NLP, time-series forecasting, propensity modelling, experimental design, and causal inference.
∙ Experience delivering AI systems in regulated industries (financial services, cybersecurity, healthcare) with SOX, GDPR, or SOC 2 compliance awareness.
∙ Expert-level Python and SQL; fluency with Google Cloud Platform, AWS, Docker, FastAPI, BigQuery, FAISS, and CI/CD tooling.
Technical Depth
∙ Ability to design hybrid retrieval architectures that balance precision (graph traversal) and semantic recall (vector similarity), with reranking layers — not just off-the-shelf RAG.
∙ Hands-on experience reducing LLM inference latency in production (e.g., redesigning pipelines from multi-minute to sub-30-second response times).
QUALIFICATIONS
∙ Master''s or PhD in Computer Science, Operations Research, Statistics, or a related quantitative field
∙ AWS Certified Machine Learning Engineer or Google Cloud Platform Professional ML Engineer certification.
∙ Completion of an AI Strategy or AI Governance programme.
∙ Prior experience at a data science / ML services firm, enterprise SaaS, or fintech — where you shipped AI to external customers, not just internal tools.
∙ Hands-on experience with Snowflake Cortex or comparable enterprise LLM deployment platforms.
∙ Open-source contributions to AI/ML tooling, published technical writing, or conference presentations.
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