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Before you apply to a job, select your language preference from the options available at the top right of this page. Explore your next opportunity at a Fortune Global 500 organization. Envision innovative possibilities, experience our rewarding culture, and work with talented teams that help you become better every day. We know what it takes to lead UPS into tomorrowpeople with a unique combination of skill + passion. If you have the qualities and drive to lead yourself or teams, there are roles ready to cultivate your skills and take you to the next level. Job Description: Job Summary We are looking for a strategic and hands-on Lead AI Platform & Automation Engineer to own and scale our enterprise AI platform capabilities. This role will serve as the primary owner of the IBM watsonx platform and Google Cloud Vertex AI platform, while providing support to GCP driving adoption, standardization, automation, and governance across the organization. The role also includes leading a team responsible for day-to-day AI model and application onboarding, pipeline automation, DevSecOps integration, BI tooling, and AI governanceincluding maintenance of IBM and vertex AI. This is a high-impact position suited for a technically solid leader who can lead technical team, architect solutions, scale platforms, and align multiple teams across engineering, data science, and business domains. Key Responsibilities Platform Leadership - Serve as the lead owner of IBM watsonx and Google Vertex AI platforms, overseeing configuration, governance, and operational maturity. - Drive platform onboarding strategy, enablement, and hands-on support across data science, engineering, and analytics teams. - Standardize reusable frameworks, templates, and infrastructure patterns for both platforms to accelerate project delivery. AI & ML Pipeline Automation - Architect and manage enterprise-wide CI/CD and MLOps pipelines for: - Model training, tuning, evaluation, and deployment - Data ingestion, transformation, and streaming - Infrastructure provisioning and teardown (IaC) - Build and maintain reusable templates for AI applications, workflows, and serving endpoints in IBM and Vertex AI. Agentic AI Enablement - Design and operationalize pipelines for Agentic AI systems using LLMs, orchestration agents, and decision engines. - Integrate intelligent agent workflows with platform capabilities and monitor lifecycle behavior and governance adherence. AI Governance (incl. ) - Implement and operationalize AI governance frameworks using IBM . - Define model approval workflows, track metadata, enforce responsible AI policies, and ensure transparency, bias detection, and explainability. - Collaborate with legal, compliance, and information security teams to embed AI governance across all AI/ML systems. DevSecOps & Automation - Integrate DevSecOps practices into pipelinesautomating vulnerability scans, access policies, and secrets management. - Embed security compliance and quality gates into all CI/CD workflows across AI and application domains. Business Intelligence & Semantic Modeling - Provide architectural guidance to BI teams using Power BI and Looker. - Oversee data modeling, semantic layer standardization, and connectivity to enterprise data lakes and warehouses. Team Leadership - Lead and mentor a cross-functional team of AI platform engineers, MLOps practitioners, BI analysts, and DevSecOps engineers. - Define goals, delivery milestones, documentation standards, and best practices for scalable operations. Qualifications Education - Bachelors or masters in computer science, Engineering, or related technical field. Experience - 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 environments. - Hands-on delivery of secure, automated pipelines using Terraform, GitOps, and containerized workflows. - Experience implementing AI governance and compliance using commercial tools and internal frameworks. - Familiarity with BI tools (Power BI, Looker) and semantic modeling techniques. Technical Skills - Platforms: IBM , , 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 Qualifications - Certifications: GCP, IBM, or Azure AI/MLOps certifications - Experience with Agentic AI systems (e.g., LangChain, IBM Orchestrate, or custom frameworks) - Familiarity with NIST, EU AI Act, or internal model risk governance frameworks - Prior experience deploying internal platform-as-a-service offerings for AI/ML Employee Type: Permanent UPS is committed to providing .
Here's where they are and how to stand out in your next interview.
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Most developer ads you'll see are written in English: 18,397 of the 24,795. That doesn't tell you whether the job itself requires you to speak English or work in English daily, so read each posting carefully. Don't assume the language of the ad matches the language of the team.
The employers posting the most developer roles are Link Group (369 jobs), Upvanta (257), jobgether (226), and OfferZen (212). If you're applying to any of these, research their hiring patterns. They move fast and post often, which means they're either scaling hard or replacing people who didn't fit.
In your interview, expect this: 'Walk me through the last time you had to debug something that took you more than an hour. What was it, what did you try first, and what would you do differently?' Hiring managers ask this to see if you think systematically or just try random fixes. Have a real example ready with specifics.