Lead AI Engineer – Search, Personalization, Agents

Job not on LinkedIn

🔥 4 minutes ago

🇲🇽 Mexico – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Hyatt

WebsiteLinkedInAll Job Openings

10,000+ employees

🍽️ Food & Beverage

✈️ Travel

🛒 Retail

Food & Beverage • Travel • Retail

Hyatt is a global hospitality company that operates a range of hotels, resorts, and vacation properties. Known for its commitment to providing exceptional guest experiences, Hyatt offers various accommodation options, from luxury to more affordable stays. The company also focuses on sustainability and community engagement, ensuring responsible business practices in the hospitality sector.

📋 Description

• Build and operate production AI systems improving Hyatt’s search, personalization, guest experiences, colleague productivity, and operational workflows • Design scalable AI systems for natural-language search, semantic retrieval, ranking, recommendations, and personalized guest experiences • Develop low-latency retrieval and ranking pipelines using keyword search, embeddings, vector retrieval, reranking, business rules, and real-time contextual signals • Partner with data scientists to productionize relevance models, recommender systems, and LLM-powered search experiences • Define experimentation approaches, relevance metrics, latency targets, A/B tests, and business-impact measurement • Lead high-throughput, low-latency LLM inference services • Optimize model serving through model selection, quantization, batching, caching, streaming, routing, autoscaling, and efficient GPU utilization • Build production APIs and services for inference, embeddings, reranking, retrieval, and agent execution • Deploy systems using AWS-native services and modern containerized infrastructure • Architect and implement agentic AI and multi-agent applications using LLMs, tools, retrieval, workflows, memory, and structured decision-making • Design orchestration patterns for planning, tool execution, state management, retries, handoffs, approvals, and fallback behavior • Establish secure agent interfaces with identity, authorization, isolation, traceability, and policy enforcement • Develop reusable agent platform components, registries, workflow templates, evaluation harnesses, and observability standards • Establish CI/CD, testing, versioning, infrastructure-as-code, reproducibility, and rollback practices • Implement observability for models and agents, including latency, availability, cost, quality, retrieval health, failures, drift, safety events, and business outcomes • Create evaluation frameworks covering benchmarks, human evaluation, adversarial testing, guardrails, bias checks, hallucination analysis, and production monitoring • Work with security, privacy, legal, architecture, and governance stakeholders to ensure safe, compliant, reliable, and responsible AI deployment • Support batch and real-time inference across the model lifecycle • Serve as hands-on technical lead for AI initiatives from discovery through production operation • Translate business opportunities into engineering problem statements, architectures, delivery plans, success metrics, and technical tradeoffs • Influence AI and ML platform roadmaps • Mentor engineers and data scientists through design reviews, code reviews, architecture discussions, and engineering best practices • Communicate technical decisions, model limitations, risks, and measured outcomes to technical and business stakeholders

🎯 Requirements

• Master’s degree in computer science, Software Engineering, or related field • 6+ years of experience in machine learning roles focused on NLP/NLU, recommender systems, or LLM applications • 4+ years of experience deploying LLMs or other Generative AI solutions to production • Expertise in AWS cloud services, including SageMaker, ECS/EKS, Step Functions, Lambda, and Glue • Expertise in TensorRT-LLM, vLLM, SGLang, HF Optimum, and ONNX runtimes • Strong programming skills in Python • Experience with SQL, PySpark, and containerization such as Docker • 6+ years of experience designing scalable data pipelines and ML systems for real-time and batch inference • Familiarity with ML observability and governance tools • Solid understanding of responsible AI practices, CI/CD pipelines, Agile development practices, and model lifecycle management • Excellent interpersonal and communication skills • Ph.D. preferred

🏖️ Benefits

• Annual allotment of free hotel stays at Hyatt hotels globally • Flexible work schedule • Work-life benefits including wellbeing initiatives such as a complimentary Headspace subscription • Discount at the on-site fitness center • Global family assistance policy with paid time off following the birth or adoption of a child • Financial assistance for adoption • Paid Time Off • Medical insurance • Dental insurance • Vision insurance • 401K with company match