Solution Lead - AI Engineer

About the role

UPS is looking for a strategic, hands-on Lead AI Platform & Automation Engineer to own and scale its enterprise AI platform. The role is the primary owner of the IBM watsonx and Google Cloud Vertex AI platforms, supporting Azure adoption, standardization, automation and governance. It also leads a team covering AI model and application onboarding, pipeline automation, DevSecOps, BI tooling and AI governance, including maintenance of watsonx.governance and Vertex AI.

Key responsibilities

• Lead IBM watsonx and Vertex AI platforms, covering configuration, governance and operational maturity, and drive onboarding, enablement and hands-on support for data science, engineering and analytics teams.
• Standardize reusable frameworks, templates and infrastructure patterns to speed up project delivery.
• Architect and run enterprise CI/CD and MLOps pipelines for model training, tuning, evaluation and deployment, data ingestion and streaming, and infrastructure provisioning (IaC).
• Build reusable templates for AI applications, workflows and serving endpoints in watsonx.ai and Vertex AI.
• Design and run pipelines for agentic AI systems using LLMs, orchestration agents and decision engines, and integrate them with platform capabilities.
• Operationalize AI governance with watsonx.governance: model approval workflows, metadata tracking, responsible AI policies, bias detection and explainability, working with legal, compliance and information security.
• Integrate DevSecOps into pipelines, automating vulnerability scans, access policies and secrets management, and embedding security compliance and quality gates in CI/CD.
• Guide BI teams on Power BI and Looker, and oversee data modeling, semantic layer standardization and connectivity to data lakes and warehouses.
• Lead and mentor a cross-functional team of AI platform engineers, MLOps practitioners, BI analysts and DevSecOps engineers, setting goals, milestones, documentation standards and best practices.

Required profile

• Bachelor's or master's degree in computer science, engineering or a related technical field.
• 8+ years in cloud engineering, MLOps or platform leadership roles.
• 3+ years leading enterprise platform delivery and infrastructure automation.
• Proven experience managing IBM watsonx and Vertex AI in production.
• Experience delivering secure, automated pipelines with Terraform, GitOps and containerized workflows.
• Experience implementing AI governance and compliance with commercial tools and internal frameworks.
• Familiarity with BI tools (Power BI, Looker) and semantic modeling.

Required skills

• Platforms: IBM watsonx.ai, watsonx.governance, Vertex AI, Azure ML
• Automation: Terraform, Ansible, GitHub Actions, GitLab CI, Azure DevOps
• Languages: Python, Bash, YAML
• Containers: Docker, Kubernetes
• ML tools: MLflow, TFX or similar
• Governance: bias detection, metadata tracking, model lineage, risk management
• Preferred: GCP, IBM or Azure AI/MLOps certifications; agentic AI frameworks such as LangChain or IBM Orchestrate; NIST, EU AI Act or model risk frameworks; prior PaaS deployments for AI/ML