Director, Software Engineering - AI Applications
Palo Alto Networks · Bengaluru · 7+ yrs experience · Posted 2026-06-08
Tech stack: AWS, Azure, Go, Google Cloud
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About the role
We are seeking a Director of Software Engineering to lead the development of next-generation Autonomous AI Agents for our Go-to-Market (GTM) and Customer Experience (CX) Applications Engineering team based in Bangalore. Responsibilities: Define the engineering vision and roadmap for Autonomous AI Agents that transform global GTM and CX workflows and operations. Lead and scale a high-performing software engineering organization delivering enterprise-grade autonomous agents and multi-agent systems using technologies such as LangGraph, AutoGen, CrewAI, Semantic Kernel, and AgentKit. Establish robust LLMOps and AI governance practices covering prompt management, vector databases, retrieval systems, evaluation frameworks, and hallucination mitigation. Partner closely with Product Management, Customer Experience, Sales Operations, Data Science, and Enterprise Architecture teams to align AI initiatives with business growth. Drive engineering excellence across architecture, reliability, scalability, observability, security, and operational readiness. Champion AI-assisted software engineering practices leveraging tools such as GitHub Copilot, Cursor, Claude Code, and internal developer copilots to modernize software delivery. Recruit, mentor, and develop engineering managers, architects, and senior engineers across globally distributed teams. Qualifications: Required Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical discipline. 15 or more years of software engineering experience, with at least 7 years leading large, globally distributed engineering organizations. Proven experience building AI copilots, autonomous agents, conversational AI, or enterprise automation platforms. Technical expertise in LLMOps, vector databases, RAG architectures, evaluation pipelines, and AI observability. Experience with frameworks such as LangGraph, Semantic Kernel, AutoGen, CrewAI, LangChain, or AgentKit. Proven experience building and scaling distributed, cloud-native enterprise platforms, microservices, and event-driven systems. Experience delivering enterprise-grade SaaS products or platforms supporting GTM, CRM, CX, or workflow automation domains. Strong experience with public cloud ecosystems such as Azure, AWS, or Google Cloud. Preferred Qualifications Proven experience building applications specifically designed for GTM motions, customer success, and support. Extensive knowledge of operational workflows, enterprise tools, and the opportunity-to-cash lifecycle. Familiarity with Responsible AI, AI governance, security, compliance, and privacy frameworks. Experience driving engineering productivity transformations using AI-assisted development tools.
Qualifications
- Required Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical discipline.
- 15 or more years of software engineering experience, with at least 7 years leading large, globally distributed engineering organizations.
- Proven experience building AI copilots, autonomous agents, conversational AI, or enterprise automation platforms.
- Technical expertise in LLMOps, vector databases, RAG architectures, evaluation pipelines, and AI observability.
- Experience with frameworks such as LangGraph, Semantic Kernel, AutoGen, CrewAI, LangChain, or AgentKit.
- Proven experience building and scaling distributed, cloud-native enterprise platforms, microservices, and event-driven systems.
- Experience delivering enterprise-grade SaaS products or platforms supporting GTM, CRM, CX, or workflow automation domains.
- Strong experience with public cloud ecosystems such as Azure, AWS, or Google Cloud.
- Proven experience building applications specifically designed for GTM motions, customer success, and support.
- Extensive knowledge of operational workflows, enterprise tools, and the opportunity-to-cash lifecycle.
- Familiarity with Responsible AI, AI governance, security, compliance, and privacy frameworks.
- Experience driving engineering productivity transformations using AI-assisted development tools.
Responsibilities
- Define the engineering vision and roadmap for Autonomous AI Agents that transform global GTM and CX workflows and operations.
- Lead and scale a high-performing software engineering organization delivering enterprise-grade autonomous agents and multi-agent systems using technologies such as LangGraph, AutoGen, CrewAI, Semantic Kernel, and AgentKit.
- Establish robust LLMOps and AI governance practices covering prompt management, vector databases, retrieval systems, evaluation frameworks, and hallucination mitigation.
- Partner closely with Product Management, Customer
- Experience, Sales Operations, Data Science, and Enterprise Architecture teams to align AI initiatives with business growth.
- Drive engineering excellence across architecture, reliability, scalability, observability, security, and operational readiness.
- Champion AI-assisted software engineering practices leveraging tools such as GitHub Copilot, Cursor, Claude Code, and internal developer copilots to modernize software delivery.
- Recruit, mentor, and develop engineering managers, architects, and senior engineers across globally distributed teams.