{"id":2175162,"url":"https://alion.io/job/united-airlines-sr-manager-ai-platform-engineering","title":"Sr. Manager, AI Platform Engineering","company":{"id":18409,"name":"United Airlines","domain":"united.com","url":"https://alion.io/company/united","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":{"grade":"A","score":100,"open_postings":16,"ghost_share":0,"stale_share":0.188,"repost_share":0,"time_to_fill_p50_days":7,"computed_at":"2026-10-17T05:46:00Z"}},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Chicago, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":147060,"max":191516,"currency":"USD","period":"year","gross":null,"usd_annual":191516},"salary_estimate":null,"experience_years_min":10,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AIOps","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Anthropic","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Feature Store","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GitOps","optional":false},{"name":"Hugging Face","optional":false},{"name":"Jenkins","optional":false},{"name":"KServe","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"OpenAI","optional":false},{"name":"RAG","optional":false},{"name":"Terraform","optional":false},{"name":"Vertex AI","optional":false}],"status":"live","first_seen_at":"2026-10-09T13:55:23Z","employer_posted_date":"2026-10-12","last_verified_at":"2026-10-17T17:48:42Z","board_verified":true,"closed_at":null,"days_open":8,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":8},"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.\nDescription\nUnited'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.\nJob overview and responsibilities\nThis role will drive architecture, development, and operations of our ML engineering and GenAI systems, enabling scalable and responsible AI solutions across the business.\nThis 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\nThe 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.\n Strategic Leadership & Platform Ownership:Define and execute the ML/GenAI platform strategy aligned with enterprise digital transformation objectives\nHands-on experience leading a Generative AI and AI Agents\nOwn the platform roadmap, architecture decisions, and budget planning to scale AI capabilities across the enterprise\nCollaborate with CDO, CIO, and senior stakeholders to identify, prioritize, and fund impactful AI/GenAI investments\nRepresent the ML Center of Excellence (COE) in cross-functional meetings and strategic planning forums\nCommunicate strategy, progress, and outcomes to executive stakeholders through clear presentations and business narratives\nServe as the primary liaison between the COE and business units, effectively communicating technical capabilities and business impact\n\n GenAI & LLM Strategy:Lead initiatives around LLMs and foundation models (e.g., OpenAI, Anthropic, and Hugging Face)\nDesign and operationalize GenAI pipelines (e.g., RAG, prompt orchestration, fine-tuning, and safety guardrails)\nWork with AI engineers to help them drive the architecture, design, and implementation of key components of the Agentic AI and Machine Learning platform\nBuild and deploy secure, scalable GenAI applications with a strong emphasis on privacy, safety, and compliance\nIntegrate LLMs into enterprise workflows, such as copilots, document summarization, intelligent assistants, and domain-specific Q&A systems\nPartner 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\n\nGenAI Engineering & AIOps:Design, manage, and monitor the enterprise AI engineering platform, ensuring scalability, reliability, and automation\nTake ownership of observability, and resilient architecture\nDevelop robust AIOps processes to monitor model performance, detect drift, and automate retraining and validation\nBuild and maintain tools and frameworks to govern GenAI models for compliance, bias, versioning, traceability, and auditability\n\nData Engineering & Feature Platforms:Design and implement feature engineering and data pipelines to deliver high-quality training data and inference-ready datasets\nPartner with data scientists and engineers to create reusable, production-grade feature stores and pipelines\nSolve complex data ingestion, transformation, and governance challenges in collaboration with data platform and DataOps teams\nDevelop integrated ML/AI solutions on enterprise analytics platforms\n\nTeam Leadership & Talent Development:Hire, mentor, and grow a high-performing AI engineering team with a focus on innovation, execution, and impact\nProvide technical mentorship and guidance to AI engineers and data scientists, ensuring high standards in design and implementation\nPromote a culture of continuous learning, experimentation, and operational excellence.\n\n Building auto-scaling ML systems:AI Engineering & AIOpsMLflow, KServe, SageMaker, Vertex AI, Databricks, etc.\n\nGenAILLM providers (OpenAI, Anthropic), Hugging Face, LangChain, Agentic Frameworks, Agent Evaluations, etc.\n\nData InfraSpark, Kafka, Delta Lake, etc\n\nDevOpsKubernetes, Jenkins, GitOps, Terraform, etc\n\nQualifications\nWhat’s needed to succeed (Minimum Qualifications):\nBachelor's degree in Computer Science, Data Science, Engineering or related field\n5+ years of experience leading product or technical teams and delivering large-scale initiatives\n2+ years of Gen AI experience\nProven experience guiding cross-functional teams through complex, multi-stakeholder programs\nMust be legally authorized to work in the United States for any employer without sponsorship\nSuccessful completion of interview required to meet job qualification\nReliable, punctual attendance is an essential function of the position\nWhat will help you propel from the pack (Preferred Qualifications):\nMaster's degree\n10+ years of experience delivering large-scale initiatives\nThe base pay range for this role is $147,060.00 to $191,516.00.\nThe 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.\nYou 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.\nUnited 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. 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