Staff IT Software Engineer, Full Stack (Java / React / GCP AI)
Palo Alto Networks · Bengaluru · 3+ yrs experience · Posted 2026-07-10
Tech stack: Cassandra, GCP, Go, Google Cloud, Java, Jenkins, Kubernetes, MongoDB, MySQL, Next.js, Node.js, Python, React, SQL, Spring Boot, TypeScript
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About the role
Design, build, and scale highly available, secure backend microservices alongside modern, performance-optimized, and responsive frontends. Design, orchestrate, and deploy production-ready agentic workflows that leverage LLM reasoning, prompt engineering, and Retrieval-Augmented Generation (RAG) for independent decision-making and complex task execution. Develop core full-stack components that interface with Generative AI model deployment and real-time inference systems. Optimize large-scale AI interactions for performance, low latency, and high throughput. Establish long-term architectural patterns and tooling choices for our Java, Next.js, and Google Cloud ecosystem, preferably GCP Vertex AI or equivalent. Champion design standards, rigorous type safety, automated testing, and comprehensive monitoring across decoupled repositories, UI components, and AI inference pipelines. Ensure all full-stack applications and integrated AI systems comply with enterprise security policies, data privacy standards, and responsible AI principles. Lead deep technical design reviews, perform high-impact code reviews, mentor engineers, and foster a culture of engineering excellence and continuous learning. Responsibilities: Design, build, and scale highly available, secure backend microservices alongside modern, performance-optimized, and responsive frontends. Design, orchestrate, and deploy production-ready agentic workflows that leverage LLM reasoning, prompt engineering, and Retrieval-Augmented Generation (RAG) for independent decision-making and complex task execution. Develop core full-stack components that interface with Generative AI model deployment and real-time inference systems. Optimize large-scale AI interactions for performance, low latency, and high throughput. Establish long-term architectural patterns and tooling choices for our Java, Next.js, and Google Cloud ecosystem, preferably GCP Vertex AI or equivalent. Champion design standards, rigorous type safety, automated testing, and comprehensive monitoring across decoupled repositories, UI components, and AI inference pipelines. Ensure all full-stack applications and integrated AI systems comply with enterprise security policies, data privacy standards, and responsible AI principles. Lead deep technical design reviews, perform high-impact code reviews, mentor engineers, and foster a culture of engineering excellence and continuous learning. Qualifications: 3+ years of professional software engineering experience, with a proven track record of operating at a Staff, or Tech Lead level. 2+ years of hands-on experience designing, fine-tuning, and building autonomous AIagentic solutions, LLM architectures, and RAG pipelines in a production setting. Expert-level experience with Java and Spring Boot (or equivalent enterprise frameworks like Go or advanced Node.js) building resilient distributed systems and secure RESTful APIs. Experience with SQL (MySQL) and NoSQL (MongoDB, Cassandra) schema design and performance tuning. Deep experience building complex, production-grade web applications using React, TypeScript, Next.js, and Node.js. Strong understanding of SSR (Server-Side Rendering), state management, and building intuitive, responsive interfaces for data-dense AI workflows. Strong experience designing and deploying distributed systems on Google Cloud Platform, specifically using Google Kubernetes Engine (GKE) or Cloud Run, alongside modern CI/CD tools (Harness, Jenkins). A strong focus on the end-user. You understand how to handle the unique UI/UX challenges of Generative AI, such as streaming model responses, conversational state management, and elegant fallback UI states. Exceptional ability to articulate complex technical, cloud, and AI concepts to both deeply technical engineers and non-technical business stakeholders. Preferred / Bonus Points Proficiency in Python for backend development, quick AI prototyping, and data processing. Experience with open-source AI frameworks (LangChain, LlamaIndex). Google Cloud Certified Professional Cloud Architect or Professional Data Engineer. Familiarity with cybersecurity principles for AI applications.
Qualifications
- 3+ years of professional software engineering experience, with a proven track record of operating at a Staff, or Tech Lead level.
- 2+ years of hands-on experience designing, fine-tuning, and building autonomous AIagentic solutions, LLM architectures, and RAG pipelines in a production setting.
- Expert-level experience with Java and Spring Boot (or equivalent enterprise frameworks like Go or advanced Node.js) building resilient distributed systems and secure RESTful APIs.
- Experience with SQL (MySQL) and NoSQL (MongoDB, Cassandra) schema design and performance tuning.
- Deep experience building complex, production-grade web applications using React, TypeScript, Next.js, and Node.js.
- Strong understanding of SSR (Server-Side Rendering), state management, and building intuitive, responsive interfaces for data-dense AI workflows.
- Strong experience designing and deploying distributed systems on Google Cloud Platform, specifically using Google Kubernetes Engine (GKE) or Cloud Run, alongside modern CI/CD tools (Harness, Jenkins).
- A strong focus on the end-user.
- You understand how to handle the unique UI/UX challenges of Generative AI, such as streaming model responses, conversational state management, and elegant fallback UI states.
- Exceptional ability to articulate complex technical, cloud, and AI concepts to both deeply technical engineers and non-technical business stakeholders.
- Preferred / Bonus Points Proficiency in Python for backend development, quick AI prototyping, and data processing.
- Experience with open-source AI frameworks (LangChain, LlamaIndex).
- Google Cloud Certified Professional Cloud Architect or Professional Data Engineer.
- Familiarity with cybersecurity principles for AI applications.
Responsibilities
- Design, build, and scale highly available, secure backend microservices alongside modern, performance-optimized, and responsive frontends.
- Design, orchestrate, and deploy production-ready agentic workflows that leverage LLM reasoning, prompt engineering, and Retrieval-Augmented Generation (RAG) for independent decision-making and complex task execution.
- Develop core full-stack components that interface with Generative AI model deployment and real-time inference systems.
- Optimize large-scale AI interactions for performance, low latency, and high throughput.
- Establish long-term architectural patterns and tooling choices for our Java, Next.js, and Google Cloud ecosystem, preferably GCP Vertex AI or equivalent.
- Champion design standards, rigorous type safety, automated testing, and comprehensive monitoring across decoupled repositories, UI components, and AI inference pipelines.
- Ensure all full-stack applications and integrated AI systems comply with enterprise security policies, data privacy standards, and responsible AI principles.
- Lead deep technical design reviews, perform high-impact code reviews, mentor engineers, and foster a culture of engineering excellence and continuous learning.