Senior Staff Software Development Engineer

Zscaler

. 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 .

Posted 9/17/2026full-timeRemote • California • United StatesSenior💰 $180,000 - $225,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and deploying secure AI solutions, integrating modern AI architecture components, and collaborating with business stakeholders to translate needs into actionable plans. Proficient in Python and experienced in managing AI systems' security and performance across major cloud platforms.

Highest-signal resume keywords

AI Solution DesignPython ProficiencyCloud Platform DeploymentAI System SecurityCollaboration with Business Stakeholders

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Architecture ComponentsRetrieval-Augmented GenerationStructured Data QueryingUnstructured Data MiningAgentic WorkflowsModel Context Protocol (MCP)Agent-to-Agent (A2A) FrameworksAutomated Evaluation FrameworksGraph-Based Knowledge SystemsRegression Testing

Soft Skills

MentoringCommunicationCollaboration

Tools & Technologies

AWSGCPAzureAPIsRelational DatabasesVector Databases

Industry Keywords

AIMachine LearningData SecurityMonitoring and Evaluation FrameworksLeast-Privilege Access

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformPython

About the role

Key responsibilities & impact

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
Establish monitoring and evaluation frameworks, implement least-privilege access, and manage ROI, cost attribution, and support plans for deployments
Expand reusable building blocks, reference architectures, skills, and engineering playbooks while mentoring team members

Requirements

What you’ll need

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

Benefits

Comp & perks

Various health plans
Time off plans for vacation and sick time
Parental leave options
Retirement options
Education reimbursement
In-office perks