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AI/ML Technical Capability Owner — Center of Excellence (Co E)TE Connectivity is evolving from product-by-product AI delivery to an AI Center of Excellence (Co E) model that democratizes AI/ML for both business and technical users in FY26. We’re hiring a Technical Capability Owner to define our technical “golden paths,” reference architectures, and persona-approved toolsets across AWS and Databricks. You’ll be the connective tissue between enterprise architecture, data science, security, and business units, designing frameworks, enabling scaled adoption, and presenting compellingly to audiences from engineering guilds to executives. You will be democratizing AI/ML for technical users, giving developers the tools, frameworks, guidance, and trainings to develop AI/ML solutions on their own. The AI/ML Technical Capability Owner will also measure value of technical tools and products developed on those tools. Own the technical capability roadmap for the AI/ML Co E; understand technical user needs on AI capabilities, align with the Business Capability Owner on outcomes, funding, chargeback model, governance, and adoption plans. Translate company goals into technical guardrails, accelerators, and “opinionated defaults” for AI/ML delivery. Design and maintain end-to-end reference architectures on AWS and Databricks (batch/streaming, feature stores, training/serving, RAG/Gen AI, Agentic AI). Publish reusable blueprints (modules, templates, starter repos, CICD pipelines) and define golden paths for each persona (Data Scientist, ML Engineer, Data Engineer, Analytics Engineer, Software Engineer, TE Citizen AI/ML Developer). Curate the best-fit suite of tools across data, ML, Gen AI, and MLOps/LMMOps (e.g., AWS S3, EKS/ECS, Lambda, Step Functions, Cloud Watch, IAM/KMS; Governance, Risk & Compliance Define technical guardrails for data security (Structured and Unstructured Data), lineage, access control, PII handling, and model risk management in accordance with TE’s AI policy. Identifying enhancements or improvements to TE’s AI Policy based on user feedback. Establish standards for experiment tracking, model registry, approvals, monitoring, and incident response. Enablement & Community Lead large cross-functional workshops; organize engineering guilds, office hours, and “train-the-trainer” programs. Present roadmaps and deep-dive tech talks to execs and engineering communities; 8–12+ years in data/ML platform engineering, ML architecture, or similar; 3+ years designing on AWS and Databricks at enterprise scale. ~ Proven experience defining reference architectures , golden paths, and reusable accelerators. ~ Strong MLOps experience: experiment tracking (MLflow), CI/CD for ML, feature stores, model serving, observability (data & model), drift/quality, A/B or shadow testing. ~ Gen AI experience: Security-by-design mindset (IAM/KMS, network segmentation, data classification, secrets, compliance frameworks). ~ Track record organizing large groups (guilds, communities of practice, multi-team workshops) and influencing without authority. ~ AWS certifications (e.g., Solutions Architect, Machine Learning Specialty); Databricks Lakehouse/ML certifications. Experience with Kubernetes/EKS, Ia C (Terraform), Delta Live Tables/Workflows, Unity Catalog policies. Background in manufacturing/industrial Io T/edge helpful. Adoption: ≥70% of AI/ML initiatives using Co E golden paths and persona-approved tooling. Time-to-value: 30–50% reduction in time to first production model or Gen AI workload. Quality & Risk: ≥90% compliance with model governance controls; Enablement: 4+ reusable blueprints and 2+ shared services in production; Inventory current tools/initiatives; run 2 enablement workshops; We’re building an AI Center of Excellence to democratize AI/ML across TE Connectivity. As our AI/ML Technical Capability Owner , you’ll define the architectures, tools, and guardrails that help teams ship reliable ML and Gen AI solutions at scale on AWS + Databricks . If you love creating golden paths, enabling large technical communities, and presenting your vision from deep dives to the boardroom, we’d love to talk.