Gartner

Lead AI Engineer (ML Ops)

Gartner • $116K — $170K *
Irving, TX 75061In-Person
Enterprise Technology
Less than 5 years of experience
Today
Be an Early Applicant
Job Overview by Ladders

Qualifications

  • 4+ years of experience in AI/ML engineering with a focus on production environments.
  • Proficient in MLOps and LLMOps platforms like MLflow and Kubernetes.
  • Strong DevOps experience, especially with containerization and CI/CD automation.
  • Advanced programming skills in Python and knowledge of ML frameworks.
  • Experience with cloud platforms and AI/ML services (AWS, Azure, GCP).
  • Expert in model monitoring and performance optimization for production systems.
  • Strong understanding of data engineering pipelines and real-time processing architectures.

Responsibilities

  • Lead the AI/ML model productionalization lifecycle with MLOps and LLMOps.
  • Architect scalable AI infrastructure integrated with enterprise platforms.
  • Define best practices for AI model lifecycle management.
  • Build production-ready AI systems for advanced analytics integration.
  • Mentor engineering teams and promote expertise in AI engineering.
  • Develop automated frameworks for model validation and monitoring.
  • Collaborate with data science to operationalize experimental AI models.

Benefits

  • Limitless growth and learning opportunities.
  • Collaborative and positive work culture with a diverse team.
  • Flexible work-from-home options as well as dynamic office collaborations.
  • 20+ PTO days plus holidays and floating holidays in the first year.
  • Comprehensive medical, dental, and vision insurance package.
  • 401K with corporate match and immediate vesting.
  • Health-and-wellness allowance programs and parental leave.
Full Job Description
About the Role: Lead AI Engineer

We are seeking a Lead AI Engineer to spearhead the end-to-end productionalization of AI initiatives across Gartner. This pivotal role blends deep expertise in AI engineering with hands-on experience in MLOps, LLMOps, and DevOps, enabling the design, deployment, and scaling of enterprise-grade AI solutions that underpin our Consulting & Insight Technology strategy.

Key Responsibilities:
  • Lead the full lifecycle of AI/ML model productionalization, establishing resilient MLOps and LLMOps pipelines for seamless model deployment, orchestration, and monitoring at scale.
  • Architect and implement scalable AI infrastructure and deployment strategies, ensuring robust integration with enterprise platforms and data ecosystems.
  • Define and enforce best practices for AI model lifecycle management, including version control, automated testing, monitoring, and CI/CD processes.
  • Build and maintain production-ready AI systems, driving the integration of advanced analytics and machine learning into core business processes.
  • Champion technical design sessions, mentor engineering teams, and cultivate expertise in modern AI engineering and MLOps tooling.
  • Develop and maintain automated frameworks for model validation, performance monitoring, and drift detection in production environments.
  • Collaborate closely with data science teams to operationalize experimental models, transforming prototypes into reliable, scalable solutions.
  • Continuously evaluate and adopt emerging technologies in AI engineering, MLOps, and LLMOps to enhance organizational AI capabilities.
  • Author comprehensive technical documentation, uphold coding standards, and ensure adherence to enterprise security, compliance, and governance requirements.

Required Qualifications:
  • 4+ years of progressive experience in AI/ML engineering, with a proven track record of deploying and scaling AI solutions in production environments.
  • High proficiency in MLOps and LLMOps platforms (e.g., MLflow, Kubeflow, Weights & Biases).
  • Strong DevOps background, including hands-on experience with containerization (Docker, Kubernetes) and CI/CD pipeline automation.
  • Advanced programming skills in Python, with deep familiarity in ML frameworks (TensorFlow, PyTorch, Scikit-learn).
  • Proficient in leveraging cloud platforms (AWS, Azure, GCP) and their native AI/ML services.
  • Solid experience in infrastructure as code (Terraform, CloudFormation) and configuration management.
  • Expertise in model monitoring, drift detection, and performance optimization for production models.
  • Strong understanding of data engineering pipelines and real-time data processing architectures.
  • Experience designing and developing APIs and working within microservices architectures.


Preferred Qualifications:
  • Experience deploying Large Language Models (LLMs) and Generative AI solutions.
  • Knowledge of AI governance, model explainability, and responsible AI practices.
  • Exposure to edge computing and advanced model optimization techniques.
  • Familiarity with vector databases and retrieval-augmented generation (RAG) architectures.
  • Experience with data mesh architectures and modern data stack technologies.
  • Background in Agile/Scrum methodologies and technical team leadership.

Who You Are:
  • Effective at managing time and meeting deadlines while leading complex AI initiatives.
  • Exceptional communicator, adept at engaging with technical teams, data scientists, and business stakeholders.
  • Highly organized, with strong multitasking, prioritization, and leadership abilities.
  • Eager to embrace and master emerging AI technologies and complex concepts rapidly.
  • Driven by intellectual curiosity and a passion for advancing AI engineering practices.
  • Demonstrated ability to deliver enterprise-scale AI projects on time, within budget, and to the highest standards of quality and reliability.


What you'll receive:
  • Competitive compensation.
  • Limitless growth and learning opportunities.
  • A collaborative and positive culture - join a diverse team of professionals that are as smart and driven as you.
  • A chance to make an impact - your work will contribute directly to our strategy.
  • Enjoy the flexibility of working from home and the energy of collaborating with peers in our dynamic offices.
  • 20+ PTO days plus holidays and floating holidays in your first year.
  • Extensive medical, dental insurance and vision plan.
  • 401K with corporate match, immediate vesting.
  • Health-and-wellness-related allowance programs.
  • Parental leave.
  • Tuition reimbursement.
  • Employee Stock Purchase Plan.
  • Employee Assistance Program.
  • Gartner Gives Charity Match.

And much more!

#LI-JD6

#LI-Hybrid

#LI-Technology

About Gartner

Gartner, Inc. is a research and advisory company that provides information, advice, and tools for leaders in IT, finance, HR, customer service and support, legal and compliance, marketing, sales, and supply chain functions. The company operates in more than 100 countries and has over 16,000 employees. Gartner was founded in 1979 and is headquartered in Stamford, Connecticut.
Learn more about Gartner
Size
16,600 employees
Market Cap
$26.4 billion
Industry
Business Services
Net Income
$266.7 million
Founded
1979
5 Year Trend
+14.1%
Revenue
$4 billion
NASDAQ
IT
* Ladders Estimates

Similar Jobs

Ad banner background

Get Ready For Your
Next Interview

More Jobs at Gartner

More Enterprise Technology Jobs

Find similar Lead AI Engineer (ML Ops) jobs:

NationwideIrving, TX