Solution Lead - AI Engineer

UPS is hiring a Solution Lead - AI Engineer. Level rates it ; you can apply on UPS.

Level's read on this job

On Level's scale, this AI engineer role is Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include LangChain, Vertex AI and MLflow.
Level classifies it as a lead role.
Level lists 2,000+ other open roles at UPS.

AI in this role

Lead and scale enterprise AI platforms, MLOps pipelines, and Agentic AI systems as the primary owner of IBM watsonx and Vertex AI.

LangChainVertex AIMLflowIbm WatsonxAzureWatsonx Governance

ml-opsai-safetymlopsai-governanceci-cdagentic-aiinfrastructure-as-code

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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 Azure 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 governance—including maintenance of IBM watsonx.governance and vertex AI.

This is a high-impact position suited for a technically strong 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 watsonx.ai 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. watsonx.governance)

Implement and operationalize AI governance frameworks using IBM watsonx.governance.

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 pipelines—automating 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

Bachelor’s or master’s 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 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 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 a workplace free of discrimination, harassment, and retaliation.

How we rate this

Solution Lead - AI Engineer at UPS rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Solution Lead - AI Engineer is an open job at UPS.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in IN - TDC 1 (IN110).
The job was posted on September 18, 2026.
Seniority: lead.
Applications are handled by UPS. Apply on UPS

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML OpsAI SafetyMLOpsAI GovernanceCI/CDAgentic AIInfrastructure As CodeLangChain

Also common in AI engineer jobs at this level

AI agents Machine learning AWS Generative AI RAG PyTorch

Pay

Typical AI engineer job: $183k

This posting doesn't list pay. Use the typical AI engineer figure when pay comes up. See AI engineer jobs

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
How do you think about the risk of an AI system in this kind of role failing silently?
Tell me about a project where mlops was part of your work. What did you do?
Tell me about a project where ai governance was part of your work. What did you do?
Tell me about a project where ci/cd was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: ML Ops, AI Safety, MLOps, AI Governance, and CI/CD. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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