Team Lead - MLOps / AI DevOps (AWS)
Bengaluru, Karnataka
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingLead and mentor a team of MLOps and cloud system engineers
Design secure, scalable, cost-efficient cloud and ML infrastructure on AWS
Optimize model deployment, monitoring, and lifecycle management with data scientists
Set best practices for provisioning, deployment, and security compliance
Reduce cloud costs while keeping AI solutions performing well
From the employer’s posting
Lead and manage a team of MLOps engineers and cloud system engineers
Oversee the design and implementation of secure, scalable, and cost-efficient cloud and ML infrastructure on AWS
Collaborate with data scientists and engineers to optimize model deployment, monitoring, and lifecycle management
Develop and enforce best practices for infrastructure provisioning, model deployment, and security compliance
Optimize the costs of our cloud resources while ensuring the optimal performance of our AI solutions
What you’ll bring
All qualificationsCore experience
- Bachelor’s or master’s degree in computer science, engineering, or a related field
Qualification wording
Bachelor’s or master’s degree in computer science, engineering, or a related field
Education & alternatives
Education - Bachelor’s or master’s degree in computer science, engineering, or a related field - AWS certifications (e.g., AWS Certified Solutions Architect – Professional, AWS Certified Machine Learning – Specialty)
Tools in this posting
- AWS
Source — Tool mentions in context
- 7+ years of experience in deploying and managing large-scale machine learning (ML) and generative AI applications - Strong expertise in AWS services and proficiency with infrastructure-as-code tools - Solid familiarity with CI/CD pipelines, containerization, and orchestration technologies
- Bachelor’s or master’s degree in computer science, engineering, or a related field - AWS certifications (e.g., AWS Certified Solutions Architect – Professional, AWS Certified Machine Learning – Specialty) Responsibilities
- Lead and manage a team of MLOps engineers and cloud system engineers, ensuring alignment with strategic AI initiatives - Oversee the design and implementation of secure, scalable, and cost-efficient cloud and ML infrastructure on AWS - Collaborate with data scientists and engineers to optimize model deployment, monitoring, and lifecycle management
About the Team Moody’s Ratings’ AI Analytics group develops advanced machine learning (ML) and generative AI solutions for high-profile data science initiatives. The successful candidate will guide teams in building robust, scalable, and secure solutions on AWS. The successful candidate will strive to meet Moody’s values: openness, diversity, inclusivity, respect, and a willingness to learn. Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.
Posting record
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- Live
- First seen by us
- Sep 22, 2026 · 32 days ago
- Recorded sightings
- 137
- Last seen by us
- Oct 24, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on careers.moodys.com. The employer’s form will show what is required.
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Job description
At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.
If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.
Skills and Competencies
- 7+ years of experience in deploying and managing large-scale machine learning (ML) and generative AI applications
- Strong expertise in AWS services and proficiency with infrastructure-as-code tools
- Solid familiarity with CI/CD pipelines, containerization, and orchestration technologies
- In-depth knowledge of ML/AI infrastructure and adherence to security best practices
- Proven track record of managing teams and delivering complex technical projects
- Excellent communication, leadership, and problem-solving skills
- Deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation and operational efficiency. Strong experience using AI tools to lead innovation initiatives. Demonstrated leadership in managing AI-related risks, ensuring ethical governance, and fostering a culture of responsible AI adoption across the organization
Education
- Bachelor’s or master’s degree in computer science, engineering, or a related field
- AWS certifications (e.g., AWS Certified Solutions Architect – Professional, AWS Certified Machine Learning – Specialty)
Responsibilities
- Lead and manage a team of MLOps engineers and cloud system engineers, ensuring alignment with strategic AI initiatives
- Oversee the design and implementation of secure, scalable, and cost-efficient cloud and ML infrastructure on AWS
- Collaborate with data scientists and engineers to optimize model deployment, monitoring, and lifecycle management
- Develop and enforce best practices for infrastructure provisioning, model deployment, and security compliance
- Drive continuous improvement in operational processes, leveraging automation and infrastructure-as-code tools
- Optimize the costs of our cloud resources while ensuring the optimal performance of our AI solutions
- Foster a culture of teamwork, openness, and innovation within and across teams
- Mentor and develop team members, promoting professional growth and skill enhancement
About the Team
Moody’s Ratings’ AI Analytics group develops advanced machine learning (ML) and generative AI solutions for high-profile data science initiatives. The successful candidate will guide teams in building robust, scalable, and secure solutions on AWS. The successful candidate will strive to meet Moody’s values: openness, diversity, inclusivity, respect, and a willingness to learn.
Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.
Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.
For more information on the Securities Trading Program, please refer to the Securities Trading Policy on Moody’s Compliance Expo page
Please note: STP categories are assigned by the hiring teams and are subject to change over the course of an employee’s tenure with Moody’s.
Source details
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- Pay
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- Location & working pattern
Bengaluru, Karnataka
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