AI Engineer, Agentic Systems (Quality Engineering)

Bot Jobs; Bengaluru; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

Palo Alto Networks is seeking an AI Engineer for Agentic Systems (Quality Engineering) in Bengaluru. The role focuses on building AI-driven QA automation and an enterprise IT SDLC ecosystem within an AI-First culture.

You will work with LangGraph, LangChain and related tools to connect Salesforce, SAP, and custom applications, while ensuring safety, observability and scalable performance in a complex enterprise environment.

Qualifications

• Build agentic features using LangGraph, ADK, LangChain, AutoGen or CrewAI, including planner/executor loops, state handling and failure recovery.
• Enable cross-system integration and tool calling across enterprise applications, including Salesforce, SAP, and custom apps.
• Build context grounding and RAG pipelines using vector stores like pgvector, Pinecone and Weaviate for current enterprise context.
• Define tools and schemas with well-specified JSON function schemas to support deterministic tool calls.

Responsibilities

• Develop and maintain agent workflows for automated testing and AI-driven IT workflows.
• Establish guardrails and human-in-the-loop processes for safe interactions with systems of record.
• Instrument agents with tracing and metrics to monitor performance and costs.

Job description

AI Engineer, Agentic Systems (Quality Engineering)

Bangalore, Karnātaka, India

IT

Ref ID: JR-022096

Our Mission

At Palo Alto Networks®, we're united by a shared mission—to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you're ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you're in the right place.

Who We Are

In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us!

We believe collaboration thrives in person. That's why most of our teams work from the office full time, with flexibility when it's needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes.

Job Summary

As a Staff Software Engineer in IT Quality Engineering Automation, you will be the technical anchor and visionary for our automated testing and next-generation SDLC ecosystem, operating directly from our Bangalore office. At Palo Alto Networks, we are transitioning from traditional QA to an AI-First engineering culture.

We are looking for an early-in-career AI Engineer to build and ship custom Agentic AI. Applications across an Enterprise IT landscape spanning Salesforce, SAP, custom. Licensing and Entitlement management applications, and AI Custom Quoting, Provisioning and ITSM platforms. You will work with modern generative AI — LLM orchestration, autonomous agent loops, tool calling and RAG — against real enterprise infrastructure, building agents that carry out multi-step business workflows, act on data across these systems through their APIs, and hand back to a human when they should.

At Palo Alto Networks we are moving towards an AI-First engineering culture, and you will not be starting from a blank page. You will build on our own internal AI platform tools for test generation, automation scripting, execution and quality reporting.

Agentic Systems & Enterprise Integration

• Build agentic features: Develop and maintain agent workflows using LangGraph, ADK, LangChain, AutoGen or CrewAI, including planner/executor loops, state handling and failure recovery.
• Enable cross-system integration and tool calling: Connect agents across enterprise applications, including: Salesforce: REST/SOAP APIs, Webhooks, Platform Events, Apex Invocable Methods, SOQL and Flows. SAP: OData/BAPI services and business-object events. Custom applications: Licensing, Entitlement, AI Custom Quoting, Provisioning and ITSM through REST APIs, webhooks and message queues.
• Build context grounding and RAG pipelines: Use vector stores such as pgvector, Pinecone and Weaviate to provide LLMs with accurate, current enterprise context.
• Define tools and schemas: Create well-specified tool definitions and JSON function schemas, including MCP tools, to support deterministic tool calls and traceability back to Jira.

Agent Quality, Safety & Observability

• Build evaluation suites: Develop and run golden-set evaluations to validate improvements to agents and prompts before release.
• Implement guardrails and human-in-the-loop workflows: Establish safety controls, rate limiting, fallbacks and clear approval handoffs, especially when agents write to systems of record.
• Enable observability: Instrument agents with tracing and metrics covering execution paths, latency, context usage and token costs, and use findings to improve performance.
• Apply responsible AI practices: Follow company policies on intellectual property and data privacy, keep secrets in managed stores and require explicit opt-in for steps that send content to external services.