IT Software Engineer
Palo Alto Networks, Inc. (company site, opens in a new tab)BengaluruOn-siteDirect career pageEst. 20–40 LPA
Posted 10h ago
Reach people at Palo Alto Networks, Inc.
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Palo Alto Networks, Inc. you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design, build, and deploy autonomous AI agents and multi-agent workflows to automate enterprise operations using frameworks like LangChain and AutoGen.
- Integrate Large Language Models with enterprise databases, APIs, and tools adhering to security and compliance standards, including building evaluation and observability frameworks.
- Own end-to-end engineering responsibilities including prompt orchestration, tool integration, safety guardrails, debugging AI behaviors, and contributing to CI/CD pipelines for AI solutions.
Minimum Requirements
- Proficiency in Python or JavaScript/TypeScript with hands-on software engineering experience.
- Practical experience building applications with Large Language Models and agentic AI frameworks such as LangChain, LangGraph, AutoGen, or CrewAI.
- Experience connecting AI models/agents with enterprise platforms or databases such as Salesforce, ServiceNow, SAP, Workday, or Vector DBs.
- Work Experience Required: Not explicitly mentioned in the JD. Notice Period: Not explicitly mentioned.
Ideal Candidate Profile
- Experienced in production-grade AI-first engineering practices including prompt engineering, agentic memory management, and structured output parsing.
- Skilled in building secure, maintainable AI systems within enterprise environments with strong knowledge of SDLC, DevOps/DevSecOps practices, and cloud deployment.
- Comfortable handling non-deterministic AI system behaviors through structured troubleshooting, evaluation frameworks, and continuous improvement approaches.