Job description

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 DataOps 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, SageMaker, Vertex AI, Databricks, etc. • GenAI • LLM providers (OpenAI, Anthropic), Hugging Face, LangChain, Agentic Frameworks, Agent Evaluations, etc. • Data Infra • Spark, Kafka, Delta Lake, etc • DevOps • Kubernetes, Jenkins, GitOps, Terraform, etc Qualifications What’s needed to succeed (Minimum Qualifications): • Bachelor's degree in 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 JobAccommodations@united.com

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Must-haves

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

Nice-to-haves

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

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Keywords to mirror

mlaillmmachine learningkubernetes

Platform: phenom
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off

Parental Leave

Wellness