Sr. Manager, AI Platform Engineering

The Senior Manager, AI Platform Engineering at United Airlines will lead the design, development, and operation of scalable ML and GenAI systems, supporting enterprise digital transformation. Responsibilities include defining platform strategy, leading a team of ML engineers, collaborating with cross-functional teams, and ensuring secure, compliant AI solutions. The role requires a bachelor’s degree in Computer Science, Data Science, Engineering, or a related field, with at least 5 years of experience leading technical teams and 2 years of GenAI experience. Candidates must be legally authorised to work in the US and able to pass an interview. Preferred qualifications include a master’s degree and over 10 years of experience delivering large-scale initiatives. The base salary ranges from $147,060 to $191,516, with eligibility for bonuses and comprehensive benefits. The Senior Manager, AI Platform Engineering at United Airlines Digital Technology leads the architecture, development, and operations of advanced ML engineering and GenAI systems, driving scalable and responsible AI solutions across the enterprise. This role is responsible for defining and executing the ML/GenAI platform strategy, collaborating with cross-functional teams, and ensuring the delivery of impactful AI outcomes. The position requires hands-on leadership in LLMs, RAG pipelines, and GenAI application integration, as well as ownership of platform strategy, roadmap, and budget planning. Compensation includes a base salary range of $147,060.00 to $191,516.00, eligibility for bonuses and long-term incentives, and a comprehensive benefits package including medical, dental, vision, life, disability, parental leave, paid time off, 401(k), and flight privileges. Achieving our goals starts with supporting yours. Grow your career, access top-tier health and wellness benefits, build lasting connections with your team and our customers, and travel the world using our extensive route network.

Come join us to create what’s next. Let’s define tomorrow, together.

Description

United's Digital Technology team is comprised of many talented individuals all working together with cutting-edge technology to build the best airline in the history of aviation. Our team designs, develops and maintains massively scaling technology solutions brought to life with innovative architectures, data analytics, and digital solutions.

Job overview and responsibilities

This role will drive architecture, development, and operations of our ML engineering and GenAI systems, enabling scalable and responsible AI solutions across the business.

This role requires a deep understanding of ML infrastructure and MLOps, combined with hands-on or architectural experience in LLMs, RAG pipelines, and GenAI application integration
The position involves leading a team of ML engineers and collaborating cross-functionally with Data Science, Data Engineering, DevOps, and business units to deliver impactful AI outcomes at scale.

• Strategic Leadership & Platform Ownership:

• Define and execute the ML/GenAI platform strategy aligned with enterprise digital transformation objectives

• Hands-on experience leading a Generative AI and AI Agents

• Own the platform roadmap, architecture decisions, and budget planning to scale AI capabilities across the enterprise

• Collaborate with CDO, CIO, and senior stakeholders to identify, prioritize, and fund impactful AI/GenAI investments

• Represent the ML Center of Excellence (COE) in cross-functional meetings and strategic planning forums

• Communicate strategy, progress, and outcomes to executive stakeholders through clear presentations and business narratives

• Serve as the primary liaison between the COE and business units, effectively communicating technical capabilities and business impact

• GenAI & LLM Strategy:

• Lead initiatives around LLMs and foundation models (e.g., OpenAI, Anthropic, and Hugging Face)

• Design and operationalize GenAI pipelines (e.g., RAG, prompt orchestration, fine-tuning, and safety guardrails)

• Work with AI engineers to help them drive the architecture, design, and implementation of key components of the Agentic AI and Machine Learning platform

• Build and deploy secure, scalable GenAI applications with a strong emphasis on privacy, safety, and compliance

• Integrate LLMs into enterprise workflows, such as copilots, document summarization, intelligent assistants, and domain-specific Q&A systems

• Partner with business leaders to identify opportunities where Agentic AI and Machine Learning can create measurable value. Translate business needs into clear AI solution designs, including guardrails, validation approaches, and measurable success metrics

• GenAI Engineering & AIOps:

• Design, manage, and monitor the enterprise AI engineering platform, ensuring scalability, reliability, and automation

• Take ownership of observability, and resilient architecture

• Develop robust AIOps processes to monitor model performance, detect drift, and automate retraining and validation

• Build and maintain tools and frameworks to govern GenAI models for compliance, bias, versioning, traceability, and auditability

• Data Engineering & Feature Platforms:

• Design and implement feature engineering and data pipelines to deliver high-quality training data and inference-ready datasets

• Partner with data scientists and engineers to create reusable, production-grade feature stores and pipelines

• Solve complex data ingestion, transformation, and governance challenges in collaboration with data platform and Data Ops teams

• Develop integrated ML/AI solutions on enterprise analytics platforms

• Team Leadership & Talent Development:

• Hire, mentor, and grow a high-performing AI engineering team with a focus on innovation, execution, and impact

• Provide technical mentorship and guidance to AI engineers and data scientists, ensuring high standards in design and implementation

• Promote a culture of continuous learning, experimentation, and operational excellence.

• Building auto-scaling ML systems:

• AI Engineering & AIOps

• MLflow, KServe, Sage Maker, Vertex AI, Databricks, etc.

• GenAI

• LLM providers (OpenAI, Anthropic), Hugging Face, Lang Chain, Agentic Frameworks, Agent Evaluations, etc.

• Data Infra

• Spark, Kafka, Delta Lake, etc

• DevOps

• Kubernetes, Jenkins, Git Ops, Terraform, etc

Qualifications

What’s needed to succeed (Minimum Qualifications):

• Bachelor's degree

Computer Science, Data Science, Engineering or related field

• 5+ years of experience leading product or technical teams and delivering large-scale initiatives
• 2+ years of Gen AI experience
• Proven experience guiding cross-functional teams through complex, multi-stakeholder programs
• Must be legally authorized to work in the United States for any employer without sponsorship
• Successful completion of interview required to meet job qualification
• Reliable, punctual attendance is an essential function of the position

What will help you propel from the pack (Preferred Qualifications):

• Master's degree
• 10+ years of experience delivering large-scale initiatives

The base pay range for this role is $147,060.00 to $191,516.00.
The base salary range/hourly rate listed is dependent on job-related, factors such as experience, education, and skills. This position is also eligible for bonus and/or long-term incentive compensation awards.

You may be eligible for the following competitive benefits: medical, dental, vision, life, accident & disability, parental leave, employee assistance program, commuter, paid holidays, paid time off, 401(k) and flight privileges.

United Airlines is an Equal Opportunity Employer. We recruit, employ, train, compensate, and promote without regard to race, color, religion, national origin, gender identity, sexual orientation, disability, age, veteran status, or any other protected category under applicable law. We provide reasonable accommodations for applicants and employees with disabilities. To request an accommodation, contact [Job Accommodations@united.com](mailto:Job Accommodations@united.com)

United's Digital Technology team is comprised of many talented individuals all working together with cutting-edge technology to build the best airline in the history of aviation. Our team designs, develops and maintains massively scaling technology solutions brought to life with innovative architectures, data analytics, and digital solutions.

Job overview and responsibilities

This role will drive architecture, development, and operations of our ML engineering and GenAI systems, enabling scalable and responsible AI solutions across the business.

This role requires a deep understanding of ML infrastructure and MLOps, combined with hands-on or architectural experience in LLMs, RAG pipelines, and GenAI application integration
The position involves leading a team of ML engineers and collaborating cross-functionally with Data Science, Data Engineering, DevOps, and business units to deliver impactful AI outcomes at scale.

• Strategic Leadership & Platform Ownership:

• Define and execute the ML/GenAI platform strategy aligned with enterprise digital transformation objectives

• Hands-on experience leading a Generative AI and AI Agents

• Own the platform roadmap, architecture decisions, and budget planning to scale AI capabilities across the enterprise

• Collaborate with CDO, CIO, and senior stakeholders to identify, prioritize, and fund impactful AI/GenAI investments

• Represent the ML Center of Excellence (COE) in cross-functional meetings and strategic planning forums

• Communicate strategy, progress, and outcomes to executive stakeholders through clear presentations and business narratives

• Serve as the primary liaison between the COE and business units, effectively communicating technical capabilities and business impact

• GenAI & LLM Strategy:

• Lead initiatives around LLMs and foundation models (e.g., OpenAI, Anthropic, and Hugging Face)

• Design and operationalize GenAI pipelines (e.g., RAG, prompt orchestration, fine-tuning, and safety guardrails)

• Work with AI engineers to help them drive the architecture, design, and implementation of key components of the Agentic AI and Machine Learning platform

• Build and deploy secure, scalable GenAI applications with a strong emphasis on privacy, safety, and compliance

• Integrate LLMs into enterprise workflows, such as copilots, document summarization, intelligent assistants, and domain-specific Q&A systems

• Partner with business leaders to identify opportunities where Agentic AI and Machine Learning can create measurable value. Translate business needs into clear AI solution designs, including guardrails, validation approaches, and measurable success metrics

• GenAI Engineering & AIOps:

• Design, manage, and monitor the enterprise AI engineering platform, ensuring scalability, reliability, and automation

• Take ownership of observability, and resilient architecture

• Develop robust AIOps processes to monitor model performance, detect drift, and automate retraining and validation

• Build and maintain tools and frameworks to govern GenAI models for compliance, bias, versioning, traceability, and auditability

• Data Engineering & Feature Platforms:

• Design and implement feature engineering and data pipelines to deliver high-quality training data and inference-ready datasets

• Partner with data scientists and engineers to create reusable, production-grade feature stores and pipelines

• Solve complex data ingestion, transformation, and governance challenges in collaboration with data platform and Data Ops teams

• Develop integrated ML/AI solutions on enterprise analytics platforms

• Team Leadership & Talent Development:

• Hire, mentor, and grow a high-performing AI engineering team with a focus on innovation, execution, and impact

• Provide technical mentorship and guidance to AI engineers and data scientists, ensuring high standards in design and implementation

• Promote a culture of continuous learning, experimentation, and operational excellence.

• Building auto-scaling ML systems:

• AI Engineering & AIOps

• MLflow, KServe, Sage Maker, Vertex AI, Databricks, etc.

• GenAI

• LLM providers (OpenAI, Anthropic), Hugging Face, Lang Chain, Agentic Frameworks, Agent Evaluations, etc.

• Data Infra

• Spark, Kafka, Delta Lake, etc

• DevOps

• Kubernetes, Jenkins, Git Ops, Terraform, etc

What’s needed to succeed (Minimum Qualifications):

• Bachelor's degree

Computer Science, Data Science, Engineering or related field

• 5+ years of experience leading product or technical teams and delivering large-scale initiatives
• 2+ years of Gen AI experience
• Proven experience guiding cross-functional teams through complex, multi-stakeholder programs
• Must be legally authorized to work in the United States for any employer without sponsorship
• Successful completion of interview required to meet job qualification
• Reliable, punctual attendance is an essential function of the position

What will help you propel from the pack (Preferred Qualifications):

• Master's degree
• 10+ years of experience delivering large-scale initiatives

Equal Opportunity Employer
The University of Missouri System is an Equal Opportunity Employer. Equal Opportunity is and shall be provided for all employees and applicants for employment on the basis of their demonstrated ability and competence without unlawful discrimination on the basis of their race, color, national origin, ancestry, religion, sex, pregnancy, sexual orientation, gender identity, gender expression, age, disability, or protected veteran status, or any other status protected by applicable state or federal law. This policy applies to all employment decisions including, but not limited to, recruiting, hiring, training, promotions, pay practices, benefits, disciplinary actions and terminations. For more information, visit https://www.umsystem.edu/ums/hr/eeo.

• All qualified applicants will receive consideration for employment without regard to race, color, national origin, ancestry, religion, sex, pregnancy, sexual orientation, gender identity, gender expression, age, disability, or protected veteran status, or any other status protected by applicable state or federal law. Achieving our goals starts with supporting yours. Grow your career, access top-tier health and wellness benefits, build lasting connections with your team and our customers, and travel the world using Responsibilities
• Responsible for defining and executing the ML/GenAI platform strategy aligned with enterprise digital transformation objectives.
• Take ownership of the platform roadmap, architecture decisions, and budget planning to scale AI capabilities across the enterprise.
• Collaborate cross-functionally with Data Science, Data Engineering, DevOps, and business units to deliver impactful AI outcomes at scale.
• Lead efforts to define and execute the strategy for GenAI and AI Agents, including LLMs and foundation models.
• Deliver high-quality GenAI pipelines, including RAG, prompt orchestration, fine-tuning, and safety guardrails.
• Design and operationalise GenAI applications with a strong emphasis on privacy, safety, and compliance.
• Lead initiatives around LLMs and foundation models, such as OpenAI, Anthropic, and Hugging Face.
• Design, manage, and monitor the enterprise AI engineering platform, ensuring scalability, reliability, and automation.
• Hire, mentor, and grow a high-performing AI engineering team with a focus on innovation, execution, and impact. Skills
• Demonstrated experience leading product or technical teams and delivering large-scale initiatives.
• Proven experience guiding cross-functional teams through complex, multi-stakeholder programmes.
• Hands-on or architectural experience in LLMs, RAG pipelines, and GenAI application integration.
• Proficiency with MLflow, KServe, Sage Maker, Vertex AI, Databricks, and similar tools.
• Experience with GenAILLM providers such as OpenAI, Anthropic, and Hugging Face.
• Familiarity with data infrastructures including Spark, Kafka, and Delta Lake.
• Knowledge of DevOps tools such as Kubernetes, Jenkins, Git Ops, Terraform, and related frameworks.
• Ability to design and implement feature engineering and data pipelines for high-quality training data and inference-ready datasets.
• Strong skills in building and maintaining tools and frameworks for governance, compliance, and auditability of GenAI models. Education
• A Bachelor's degree in Computer Science, Data Science, Engineering, or a related field is required.
• A Master's degree is preferred.