Sr Manager, Software Engineering at Gartner

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

21 Apr, 26

Salary

0.0

Posted On

21 Jan, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Engineering, MLOps, LLMOps, DevOps, Python, TensorFlow, PyTorch, Scikit-learn, AWS, Azure, GCP, Terraform, CloudFormation, API Development, Microservices, Scrum, Data Engineering

Industry

Market Research

Description

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. 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: 10+ years of progressive experience in AI/ML engineering, with a proven track record of deploying and scaling AI solutions in production environments. Should have direct people management experience 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. Experience with Scrum software development methodology Experience in all phases of a systems development lifecycle & a proven track record of experience in leading the design and deployment of large-scale solutions Excellent problem-solving skills as well as clear and concise communication by adapting delivery to resonate with different audiences. 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 managing technical teams. 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. Who are we? At Gartner, Inc. (NYSE:IT), we guide the leaders who shape the world. Our mission relies on expert analysis and bold ideas to deliver actionable, objective business and technology insights, helping enterprise leaders and their teams succeed with their mission-critical priorities. Since our founding in 1979, we’ve grown to 21,000 associates globally who support ~14,000 client enterprises in ~90 countries and territories. We do important, interesting and substantive work that matters. That’s why we hire associates with the intellectual curiosity, energy and drive to want to make a difference. The bar is unapologetically high. So is the impact you can have here. What makes Gartner a great place to work? Our vast, virtually untapped market potential offers limitless opportunities – opportunities that may not even exist right now – for you to grow professionally and flourish personally. How far you go is driven by your passion and performance. We hire remarkable people who collaborate and win as a team. Together, our singular, unifying goal is to deliver results for our clients. Our teams are inclusive and composed of individuals from different geographies, cultures, religions, ethnicities, races, genders, sexual orientations, abilities and generations. We invest in great leaders who bring out the best in you and the company, enabling us to multiply our impact and results. This is why, year after year, we are recognized worldwide as a great place to work. What do we offer? Gartner offers world-class benefits, highly competitive compensation and disproportionate rewards for top performers. In our hybrid work environment, we provide the flexibility and support for you to thrive — working virtually when it's productive to do so and getting together with colleagues in a vibrant community that is purposeful, engaging and inspiring. Ready to grow your career with Gartner? Join us. The policy of Gartner is to provide equal employment opportunities to all applicants and employees without regard to race, color, creed, religion, sex, sexual orientation, gender identity, marital status, citizenship status, age, national origin, ancestry, disability, veteran status, or any other legally protected status and to seek to advance the principles of equal employment opportunity. Gartner is committed to being an Equal Opportunity Employer and offers opportunities to all job seekers, including job seekers with disabilities. If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to use or access the Company’s career webpage as a result of your disability. You may request reasonable accommodations by calling Human Resources at +1 (203) 964-0096 or by sending an email to ApplicantAccommodations@gartner.com. Job Requisition ID:107348 By submitting your information and application, you confirm that you have read and agree to the country or regional recruitment notice linked below applicable to your place of residence. Gartner Applicant Privacy Link: https://jobs.gartner.com/applicant-privacy-policy For efficient navigation through the application, please only use the back button within the application, not the back arrow within your browser. At Gartner, we guide the leaders who shape the world. About 14,000 client enterprises worldwide rely on Gartner for actionable, objective business and technology insights. Our teams of thinkers and doers know that staying curious is the best way to shape the future, for ourselves and our clients. Our sustained success creates limitless opportunities for you to grow professionally and flourish personally. We have a vast, virtually untapped market potential ahead of us, providing you with an exciting trajectory long into the future. How far you go is driven by your passion and performance. In our hybrid work environment, we provide the flexibility and support for you to thrive — working virtually when it's productive to do so and getting together with colleagues in a vibrant community that is purposeful, engaging and inspiring.

Responsibilities

Lead the full lifecycle of AI/ML model productionalization and establish resilient MLOps and LLMOps pipelines. Collaborate closely with data science teams to operationalize experimental models and ensure robust integration with enterprise platforms.