Manager, Software Engineering @ Palo Alto Networks

Your Career

As the Senior AI Engineering Manager, you will lead a talented team of 8 AI/ML engineers and data scientists based in India. You will be a critical leader within our global AI Enterprise Team, responsible for driving the technical vision, execution, and delivery of AI-powered solutions across Palo Alto Networks.

This is a hands-on leadership role where you will blend your deep technical expertise with your passion for mentoring and growing high-performing teams. You will partner closely with product managers, business stakeholders, and other engineering leaders to define the roadmap and deliver transformative AI initiatives. Your leadership will directly contribute to scaling our AI capabilities and embedding intelligence into the core of our business operations.

Your Impact

• Lead and Mentor: Manage and grow a team of 8 direct reports, fostering a culture of innovation, collaboration, and engineering excellence. Provide technical guidance, career development, and mentorship.
• Drive Technical Strategy: Define the technical roadmap and architecture for enterprise AI solutions, ensuring they are scalable, reliable, and aligned with business goals.
• Execute and Deliver: Oversee the end-to-end lifecycle of AI/ML projects, from ideation and model development to deployment and operational support in a fast-paced, agile environment.
• Collaborate and Influence: Work cross-functionally with teams across IT and the business to identify opportunities for AI, gather requirements, and ensure successful adoption of your teams solutions.
• Champion Best Practices: Establish and promote best practices for MLOps, data governance, model validation, and the ethical use of AI.

Your Experience

• 10+ years of experience in software engineering, with at least 5 years in the AI/ML space.
• 3+ years of formal people management experience, with a proven track record of building and leading high-performing engineering teams.
• Strong technical background in machine learning, including experience with deep learning, NLP, predictive modeling, and data science.
• Proficiency with common AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn) and programming languages (e.g., Python).
• Experience with MLOps principles and tools for building and deploying models at scale (e.g., Kubeflow, MLflow, Vertex AI, or similar platforms).
• Familiarity with cloud platforms (GCP, AWS, or Azure) and data engineering technologies (e.g., BigQuery, Spark, Kafka).
• Excellent communication and interpersonal skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.
• Bachelors or Masters degree in Computer Science, Engineering, or a related technical field