Lead AI Engineer (ML Ops)
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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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
