Lead AI Engineer (ML Ops)

GartnerStamford, CT
7h$116,000 - $170,000Hybrid

About The Position

About Gartner IT Join a world-class team of forward-thinking engineers dedicated to delivering innovative digital solutions that empower our analysts and clients. At Gartner IT, we drive organizational transformation through advanced technology, fostering a culture of continuous innovation, outcome-oriented execution, and the belief that impactful ideas can originate from any team member. 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.

Requirements

  • 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.

Nice To Haves

  • 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.

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.

Benefits

  • 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.
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