Lead AI/ML Engineering

UPS

. Lead the design and implementation of enterprise AI, analytics, and intelligent software solutions across cloud and distributed environments .

Posted 11/10/2026full-timeUnited StatesSenior💰 $108,600 - $231,084 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing enterprise AI and analytics solutions, with a strong focus on generative AI, machine learning, and cloud-native architectures. Proven ability to lead technical initiatives, mentor teams, and collaborate across diverse business and technical domains to drive scalable outcomes.

Highest-signal resume keywords

Generative AI DevelopmentMachine Learning ImplementationCloud-Native Architecture DesignAI Evaluation and TestingCI/CD and DevSecOps Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software Development Life Cycle (SDLC)AI Agents DevelopmentLarge Language Models (LLMs)Data Pipeline DesignNLP TechniquesPredictive ModelingAgile DevelopmentAutomated TestingMLOps/LLMOpsPerformance Evaluation

Soft Skills

Strong Communication SkillsMentoring Engineering TalentCollaboration Across Teams

Tools & Technologies

APIsData Integration ToolsCloud PlatformsObservability ToolsDeployment Automation Tools

Industry Keywords

Data GovernanceResponsible AI PracticesEnterprise Software SolutionsAnalytics SolutionsTechnical Leadership

Tech Stack

Tools & technologies

CloudSDLC

About the role

Key responsibilities & impact

Lead the design and implementation of enterprise AI, analytics, and intelligent software solutions across cloud and distributed environments
Translate complex business problems into scalable solutions using generative AI, agentic AI, machine learning, analytics, and automation
Lead development of AI agents and intelligent applications, including LLM integration, orchestration, retrieval-augmented generation (RAG), semantic retrieval, enterprise data, and tool integration
Establish reusable architectures, frameworks, engineering patterns, and components that accelerate delivery across business domains and use cases
Collaborate across Business, Product, Architecture, Engineering, Data Science, Data Engineering, UX, and Security to deliver enterprise AI capabilities
Lead integration of structured and unstructured enterprise data into AI, analytics, and machine learning solutions
Evaluate and apply appropriate AI and ML technologies based on business requirements
Establish AI evaluation and testing practices for grounding, accuracy, relevance, reliability, performance, regression testing, and production monitoring
Lead adoption of cloud-native architectures, APIs, data pipelines, and integration patterns supporting scalable AI and analytics workloads
Champion responsible and secure AI practices, including data governance, identity and access, privacy, traceability, auditability, and appropriate human oversight
Drive engineering excellence through CI/CD, DevSecOps, MLOps/LLMOps, automated testing, observability, deployment automation, and production operations
Lead complex technical initiatives, manage dependencies and risks, resolve technical roadblocks, and provide technical guidance across project teams
Partner with business and product stakeholders to prioritize capabilities based on business value, scalability, reuse, and measurable outcomes
Act as a technical leader and mentor, developing engineering talent and promoting modern AI and software engineering practices

Requirements

What you’ll need

8+ years of experience across the Software Development Life Cycle (SDLC) designing, building, deploying, and operating enterprise software, data, analytics, or AI solutions
Demonstrated experience leading the development and production deployment of generative AI, agentic AI, machine learning, or intelligent applications
Experience with LLMs, RAG, AI agents, orchestration, prompt engineering, semantic retrieval, and AI evaluation
Experience designing scalable cloud-native architectures, APIs, data pipelines, and enterprise integrations supporting AI solutions
Strong understanding of AI engineering practices, including grounding, evaluation, observability, performance, security, responsible AI, and MLOps/LLMOps
Experience applying ML and analytical techniques such as NLP, classification, regression, forecasting, and predictive modeling
Experience with Agile development, CI/CD, DevSecOps, automated testing, and production operations
Demonstrated ability to establish reusable engineering patterns, lead complex technical initiatives, mentor engineering talent, and collaborate across technical and business teams
Strong written and verbal communication skills with the ability to translate complex technical concepts into business outcomes
Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, Statistics, or a related technical discipline, international equivalent, or equivalent job experience
Must work in the New Jersey, Atlanta, Maryland, or Kentucky UPS IT office 3 days a week

Benefits

Comp & perks

Annual short-term and/or long-term incentive compensation programs may be available
Medical/prescription drug coverage
Dental coverage
Vision coverage
Flexible Spending Account
Health Savings Account
Dependent Care Flexible Spending Account
Basic and Supplemental Life Insurance & Accidental Death and Dismemberment
Disability Income Protection Plan
Employee Assistance Program
401(k) retirement program
Vacation
Paid Holidays and Personal time
Paid Sick and Family and Medical Leave time as required by law
Discounted Employee Stock Purchase Program
Visa sponsorship for specific positions