Sr. Staff Software Development Engineer

Zscaler is a cloud security company focused on accelerating digital transformation through its Zero Trust Exchange platform and AI-native enterprise initiatives. The Sr. Staff Software Development Engineer will build secure, production-grade AI solutions, partner with business leaders to identify opportunities and shape roadmaps, and establish engineering standards and playbooks while mentoring team members.

Responsibilities:

• Partner with business leaders and product owners from discovery through delivery to map workflows, identify high-value AI opportunities, shape roadmaps, and advise on technical feasibility, cost, and risk
• Design and ship secure, production-grade AI solutions across retrieval-augmented generation, structured data querying, unstructured data mining, and agentic workflows, integrating them with core systems of record
• Bring a product-ownership mindset to deployments by establishing monitoring and evaluation frameworks, implementing least-privilege access, and managing ROI, cost attribution, and support plans
• Set engineering standards by expanding reusable building blocks, reference architectures, skills, and engineering playbooks while mentoring team members

Requirements:

• 6+ years of professional software engineering experience, including at least 3 years working directly on AI and/or ML projects
• Hands-on experience across modern AI architecture components, including retrieval methods, reusable skill development, agentic orchestration, Model Context Protocol (MCP) integration, and agent-to-agent (A2A) frameworks
• Proven track record of direct collaboration with business stakeholders to run discovery, translate ambiguous needs into actionable plans, and communicate trade-offs, risk, cost, performance, and architecture
• Demonstrated experience securing AI systems and underlying data, including least-privilege access controls and defending against prompt injection, data leakage, and non-compliant outputs
• Strong engineering foundation proficiency in Python, with experience deploying AI at scale on major cloud platforms (AWS, GCP, Azure), integrating across APIs, relational/vector databases, and enterprise systems, and monitoring production drift and failure modes
• Familiarity with memory management and long-term context architectures for AI agents
• Direct experience with graph-based knowledge systems
• Experience building automated evaluation frameworks such as LLM-as-judge methodologies or regression testing at-scale for AI quality