Principal Software Engineer / Pmts - Fullstack

Salesforce Salesforce · Enterprise · Hyderabad, India

Salesforce's Einstein Bots & Agentforce team is seeking a Principal Software Engineer to design, build, and own end-to-end features for their AI-powered customer service platform. This role involves evolving conversational AI systems, enhancing NLU and LLM reasoning engines, and building tooling for intelligent agents. The engineer will focus on robust, low-latency systems, service health, and mentoring junior engineers, contributing to a large-scale enterprise solution impacting millions of users.

What you'd actually do

  1. Take a leading and hands-on role in driving the ideation, design and implementation of core features and modules in the platform and its services.
  2. Build components and features end to end, from product requirements to production-ready software.
  3. Work with product managers and other stakeholders in refining and preparing requirements. Work closely with developers, QA, PM and UX to ensure their features are delivered to meet business and quality requirements.
  4. Be accountable for maintaining the health of our platform services via objective measures defined (scalability, fault tolerance, high availability, extensibility, maintainability, etc.).
  5. Determines overall architectural principles, frameworks, and standards. Able to mentor and guide other engineers on best practices and technical complexities.

Skills

Required

  • Software design and architecture
  • End-to-end feature development
  • SaaS cloud environments
  • Microservices architecture
  • Mentoring junior engineers
  • Code and design reviews
  • Testing and quality assurance
  • Production support and troubleshooting
  • Conversational AI systems
  • LLM integration
  • NLU enhancement

Nice to have

  • Agent orchestration
  • Low-latency systems
  • Scalability and fault tolerance
  • Customer service automation

What the JD emphasized

  • core features
  • production-ready software
  • health of our platform services
  • architectural principles
  • micro-service multi-tenant SaaS cloud environment
  • code and design reviews
  • cross-team/cross-cloud impact
  • tools, technology and testing requirements
  • quality strategy, product, and process
  • subject matter expert
  • manual and automated testing
  • on-call rotation
  • Troubleshoot complex production issues
  • mentorship and technical guidance
  • long-term design strategies

Other signals

  • building agentic systems
  • customer service automation
  • LLM-powered reasoning engines
  • conversational AI