Welcome to Warner Bros. Discovery… the stuff dreams are made of.

Who We Are…

When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next…

From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive.

Your New Role: 
 

As the Lead – AI/ML DevSecOps, you will play a critical role in shaping the security, reliability, and efficiency of our AI and machine learning systems at one of the world’s largest Media & Entertainment companies. Operating from India, you will lead the implementation of cutting-edge DevSecOps practices tailored to the unique needs of AI/ML pipelines, ensuring scalable, secure, and high-performing AI/ML solutions that drive our global operations. 

 

This role requires an innovative and proactive leader who understands the interplay between development, security, and operations in AI/ML workflows. You will collaborate with cross-functional teams of engineers, data scientists, and business leaders to establish industry-leading best practices for AI/ML DevSecOps while ensuring compliance with the highest standards of security and governance. 

 

If you are passionate about revolutionizing AI/ML development with robust, secure, and automated pipelines, this is your opportunity to make a significant impact in a fast-paced, creative, and high-visibility environment. 

1. DevSecOps Strategy and Leadership 

Define and implement a DevSecOps strategy specifically tailored for AI/ML systems, ensuring seamless integration with existing workflows. 

Lead and mentor a high-performing team of DevSecOps engineers, fostering a culture of collaboration, automation, and continuous improvement. 

Develop and enforce security protocols and policies that align with enterprise AI/ML objectives and regulatory requirements. 

Stay ahead of industry trends and emerging technologies in AI/ML DevSecOps, incorporating relevant innovations into the organization’s workflows. 

Partner with senior leadership to align AI/ML DevSecOps initiatives with broader organizational goals. 

 

2. CI/CD Pipeline Design and Optimization for AI/ML 

Design and implement robust CI/CD pipelines for AI/ML model development, testing, and deployment, ensuring minimal downtime and maximum efficiency. 

Automate model versioning, retraining, and deployment workflows to streamline the AI/ML lifecycle. 

Collaborate with data engineering teams to integrate data pipelines into the CI/CD workflows, ensuring data readiness for model development. 

Optimize resource utilization across cloud and on-premise infrastructures to enhance performance and reduce operational costs. 

Implement monitoring and alerting mechanisms to ensure the continuous health of AI/ML pipelines. 

 

3. Security and Compliance in AI/ML Pipelines 

Embed security practices into every stage of the AI/ML lifecycle, from model training to deployment. 

Conduct regular security audits and vulnerability assessments of AI/ML pipelines, addressing gaps proactively. 

Ensure compliance with data privacy regulations (e.g., GDPR, CCPA) and industry-specific standards. 

Develop and enforce secure coding practices for AI/ML engineers, emphasizing model integrity and data protection. 

Collaborate with legal and compliance teams to address the ethical and legal considerations of AI deployment. 

 

4. Collaboration and Stakeholder Management 

Work closely with data scientists, software engineers, and product teams to understand their requirements and deliver secure, scalable solutions. 

Partner with IT and cloud infrastructure teams to manage AI/ML environments effectively. 

Provide technical leadership and guidance to teams across the organization on AI/ML DevSecOps best practices. 

Act as a liaison between technical teams and business stakeholders, ensuring alignment of AI/ML initiatives with business goals. 

Foster strong relationships with external partners, including cloud providers, security vendors, and industry forums. 

 

5. Innovation and Continuous Improvement 

Drive automation initiatives to enhance efficiency and reduce manual intervention in AI/ML workflows. 

Develop and implement tools to monitor and improve the performance, scalability, and reliability of AI/ML systems. 

Foster a culture of experimentation and learning within the team to explore new technologies and methodologies. 

Regularly review and refine DevSecOps practices to keep pace with evolving industry standards and challenges. 

Contribute to knowledge sharing and training initiatives to upskill team members and promote best practices. 

Qualifications & Experiences: 

 

Academic Qualifications: 

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field. 

Certifications in DevOps, Cloud Security, or AI/ML frameworks (e.g., AWS Certified DevOps Engineer, Kubernetes, TensorFlow, etc.) are highly desirable. 

 

Professional Experience: 

8+ years of experience in DevOps, with a strong focus on AI/ML workflows for at least 3 years. 

Proven expertise in designing, deploying, and managing CI/CD pipelines for machine learning models. 

Hands-on experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes). 

Deep understanding of AI/ML frameworks and libraries such as TensorFlow, PyTorch, and Scikit-learn. 

Strong experience in implementing security best practices and ensuring compliance in DevOps workflows. 

 

Technical Skills: 

Expertise in infrastructure as code (Terraform, Ansible, etc.) and automation tools. 

Proficiency in programming languages such as Python, Bash, and JavaScript. 

Knowledge of monitoring and logging tools like Prometheus, Grafana, or Splunk. 

Strong understanding of AI/ML model lifecycle management and deployment challenges. 

Familiarity with vulnerability management tools and practices. 

 

Other Skills: 

Excellent leadership and people management skills, with experience leading technical teams. 

Strong communication and presentation skills, with the ability to convey complex ideas to non-technical stakeholders. 

Analytical mindset with a problem-solving approach and a focus on delivering results. 

Passion for learning and staying updated on the latest trends in DevSecOps and AI/ML. 

Proven ability to work in a fast-paced, dynamic environment and manage multiple priorities effectively. 

How We Get Things Done…

This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview.

Championing Inclusion at WBD

Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law.

If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.