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Were building foundational infrastructure to secure AI agents-including their identities, access patterns, and interactions with sensitive systems and data.
This includes designing intelligent, dynamic mechanisms for ephemeral access control, secrets management, and agent and user identity tailored to the modern agent ecosystem.
As a Staff Engineer, youll take ownership of these critical systems, designing and implementing how agents establish identity, receive dynamic access, securely interact with sensitive systems, and leave verifiable audit trails. Youll shape the long-term architecture, anticipate technical risks, and evolve systems that span both machine- and human-facing workflows.
This is a rare opportunity to combine hands-on engineering with technical leadership-writing critical code, mentoring engineers, sharing knowledge, and driving best practices-while building a platform from the ground up at the cutting edge of AI, identity, and security.
Responsibilities:
Own and guide the technical direction of core platform domains, including agent identity, authentication, authorization, and secrets management,
shaping architectures that span multiple services and teams while balancing scalability, reliability, and security.
Lead by example through high-impact implementation, mentoring engineers, and helping them navigate complex technical tradeoffs.
Proactively identify critical technical problems or gaps, and drive solutions from concept through delivery.
Establish and promote engineering best practices, ensuring high standards for code quality, security, and operational excellence.
Communicate complex technical concepts clearly to engineers, architects, product managers, and stakeholders, influencing decisions, fostering alignment, and driving cross-team collaboration.
Document key decisions, patterns, and practices to elevate team knowledge and ensure consistency across the platform.
Advocate for continuous improvement and operational efficiency, helping the team work smarter while maintaining a secure, high-quality platform.

'we are looking for a Senior Software Engineer to join our team responsible for the machine identity and access offering, designing and developing services used as part of our companys SaaS products.
The team designs and develops services that integrate closely with leading cloud vendors like AWS, Azure, GCP, and many other DevOps services and tools, providing managed access to sensitive assets in the organization.
In this role, you will be using advanced AWS microservices, with Ruby, Golang, Java and Python through the entire SDLC from planning to production.
The team collaborates with security architects, product managers, and other development teams.
Together we produce complex and advanced solutions that meet the highest security standards and NFRs.
We are looking for someone energetic and versatile to join our family and help us achieve our goals.
Design and develop new features using container-based architectures
Research new technologies and platforms
Be a member of a highly talented cross-functional development team of developers, architects, and QA engineers, in an agile oriented environment
Participate in continuous and iterative engineering cycles, emphasizing code quality, supportability, scalability, and performance.

Join Palo Alto Networks IDIRA Product Management team in the exciting and rapidly emerging space of Agentic identity.
As Product Manager, you will lead the roadmap for Agentic Identity part of the IDIRA product management team. This domain is new and evolving quickly, so youll need to be comfortable with ambiguity, proactive research, and rapid execution to set the industry standard for how autonomous agents are authenticated and governed in organizations.
Develop deep expertise with identity management, authentication and authorization standards relevant to Agentic AI, and apply this knowledge to shape product strategy and execution.
Define and execute the roadmap for IDIRA - Agentic Identity solution, ensuring we set the industry standard for Agentic Identity authentication, authorization, lifecycle, and governance.
Act as the primary advocate for the developer experience ensuring security solutions smoothly integrate into programmatic agent development without friction.
Partner with customers and lead interviews to inform product direction and validate new market standards.
Work closely with other Product Managers and cross-functional units to leverage IDIRAs existing assets, align them to the Agentic Identity challenges.
Move fast and iterate-this domain is evolving rapidly, so youll need to research, validate, and execute quickly, adapting to new requirements and opportunities as they arise.
Prioritize high-impact deliveries that address urgent market demand

As a Data Science Manager, you will lead, mentor, and grow a team of applied data scientists working on machine learning models that power AI-driven cybersecurity solutions. You will own the end-to-end development lifecycle of AI projects, from exploratory research and experimentation through to scalable deployment and optimization. In this role, you will partner with engineering and product leadership to define technical strategies, prioritize initiatives, and ensure successful model delivery. You will also drive innovation across a broad spectrum of ML domains, including supervised/unsupervised learning, anomaly detection, and generative AI, while providing hands-on guidance and championing best practices in MLOps, data governance, and model evaluation.
Key Responsibilities
Lead, mentor, and grow a team of applied data scientists working on machine learning models that power AI-driven cybersecurity solutions.
Own the end-to-end development lifecycle of AI projects - from exploratory research and experimentation through scalable deployment and optimization.
Partner with engineering and product leadership to define technical strategies, prioritize initiatives, and ensure successful model delivery.
Drive innovation across a broad spectrum of ML domains including supervised/unsupervised learning, anomaly detection and generative AI.
Provide hands-on guidance in model development using tools such as scikit-learn, PyTorch, TensorFlow, and Hugging Face.
Ensure high-quality execution through strong code review practices, reproducibility, and model evaluation frameworks.
Champion best practices in MLOps, data governance, explainability, and monitoring.
Keep pace with academic and industry advances and translate cutting-edge research into productized capabilities.