Sr. Manager, AI Platform Engineering

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

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

Master's degree

10+ years of experience delivering large-scale initiatives