Staff Software Development Engineer - AI Engineer

Zscaler
India
Workplace: HybridFull timeFunction: Data Science & Machine LearningExperience: 5+ yearsEducation: bachelorsSkills: ["Ownership","Collaboration","Bias for action","End-to-end execution","Thrives in ambiguity"]

Build and scale the agentic layer of an AI-native Product Operations platform, translating ambiguous business needs into production-grade AI systems. You’ll develop end-to-end services using FastAPI, NextJS, and Postgres, applying RAG, embeddings, vector retrieval, and agent orchestration with reliable workflow state management. Own AI engineering harnesses for testing, debugging, replay, evaluation, tracing, and safe controlled experimentation while implementing scalable, observable guardrails.

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FursaFursa
Zscaler
Zscaler
2 months ago

Staff Software Development Engineer - AI Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 3 hours agoStatus: Live

Job Summary

Build and scale the agentic layer of an AI-native Product Operations platform, translating ambiguous business needs into production-grade AI systems. You’ll develop end-to-end services using FastAPI, NextJS, and Postgres, applying RAG, embeddings, vector retrieval, and agent orchestration with reliable workflow state management. Own AI engineering harnesses for testing, debugging, replay, evaluation, tracing, and safe controlled experimentation while implementing scalable, observable guardrails.
Location: India
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Sr. Manager level

Key Responsibilities

  • •Build and scale the agentic layer of the AI-native Product Operations platform using production-grade AI systems and reusable platform capabilities.
  • •Develop AI workflows using FastAPI, NextJS, and Postgres while applying RAG architectures, embeddings, vector retrieval, and agent orchestration with workflow state management.
  • •Create AI engineering harnesses for prompt testing, agent debugging, workflow replay, evaluation, regression testing, tracing, and controlled experimentation.
  • •Design and maintain graph-based agent workflows including multi-step reasoning, tool-calling paths, branching logic, human-in-the-loop checkpoints, and stateful execution patterns.
  • •Implement standards, patterns, and guardrails to keep AI development scalable, reliable, observable, and cohesive.

Pay and Benefits

Perks:Health InsurancePaid LeaveParental LeaveLearning Budget

Key Requirements

  • •5+ years of industry experience, with the last 2-3 years focused on building or working with AI development harnesses such as evaluation pipelines and workflow replay tools.
  • •Hands-on software engineering experience building end-to-end stacks with FastAPI, NextJS, and Postgres.
  • •Proven production experience building and deploying agentic AI systems using RAG, embeddings, and vector retrieval.
  • •Familiarity with prompt engineering, orchestration patterns, graph-based agent workflows, and evaluation frameworks/guardrails.
  • •Practical understanding of agentic loops including planning, retrieval, tool execution, validation, retry handling, reflection, and termination criteria.
Experience:5+ yearsAIAgentic AIRAG
Education:Bachelor's in Computer Science
Skills:OwnershipCollaborationBias for actionEnd-to-end executionThrives in ambiguity
Tech Stack:FastAPINextJSPostgresRAGEmbeddingsVector retrievalAgent orchestrationWorkflow state managementPrompt engineeringGraph-based agent workflowsPrompt or agent regression testingTracingObservabilityWorkflow replayEvaluation pipelinesRegression testing

Company Brief

Zscaler
Provides cloud-native security platform delivering secure access, threat protection, and zero trust services to organizations, enabling secure internet and private application access without traditional network appliances.
Industry: Cybersecurity
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: San Jose, United States
Founded: 2007
WebsiteLinkedIn