Sr. Director - AI Engineering
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La posizione
Lead and unify the engineering of the AI Foundations platform to enable teams to build, deploy, evaluate, experiment with, monitor, and govern AI agents and ML models at enterprise scale.
Own three core platform areas: ML Platform & Developer Productivity (training, inference, environments, cost/perf); Model & Agent Lifecycle & Governance (CI/CD, registries, lineage, access control); Agent Observability, Evaluation & Reliability (quality, drift, experimentation).
Make agent evaluation and experimentation standard platform capabilities, featuring offline evaluation, pre-deployment quality gates in CI/CD, controlled experimentation (A/B tests, canaries, shadow traffic), and continuous post-deployment monitoring.
Drive end-to-end observability across data pipelines, retrieval, model inference, tool execution, and agent outcomes, with well-defined SLIs/SLOs for quality, latency, reliability, and cost.
Standardize ML and agent development workflows to reduce time-to-production and eliminate bespoke infrastructure across teams.
Partner with Applied AI, Data Science, Product, Security, Legal, and Responsible AI to translate regulatory and business requirements into robust engineering systems, while building a high-performing organization of managers and senior engineers.
Own three core platform areas: ML Platform & Developer Productivity (training, inference, environments, cost/perf); Model & Agent Lifecycle & Governance (CI/CD, registries, lineage, access control); Agent Observability, Evaluation & Reliability (quality, drift, experimentation).
Make agent evaluation and experimentation standard platform capabilities, featuring offline evaluation, pre-deployment quality gates in CI/CD, controlled experimentation (A/B tests, canaries, shadow traffic), and continuous post-deployment monitoring.
Drive end-to-end observability across data pipelines, retrieval, model inference, tool execution, and agent outcomes, with well-defined SLIs/SLOs for quality, latency, reliability, and cost.
Standardize ML and agent development workflows to reduce time-to-production and eliminate bespoke infrastructure across teams.
Partner with Applied AI, Data Science, Product, Security, Legal, and Responsible AI to translate regulatory and business requirements into robust engineering systems, while building a high-performing organization of managers and senior engineers.
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