AI Engineer _ GitHub Copilot Agents (Salesforce Development & Testing)

AI Engineer with strong hands-on experience in building GitHub Copilot-based AI agents to accelerate Salesforce development and testing. The role will focus on leveraging agentic AI and prompt engineering to automate SDLC activities and improve delivery efficiency.

Job Description

Must Have Technical/Functional Skills

• Hands-on experience with GitHub Copilot for development and testing automation
• Proven ability to build AI agents / Copilot-driven workflows
• Strong Salesforce development experience (Apex, LWC, integrations)
• Strong Python programming skills (mandatory)
• Experience in Prompt Engineering and prompt optimization
• Experience working with LLMs (GPT, Claude, etc.)
• Knowledge of:
  • Test automation frameworks
  • SDLC lifecycle automation
  • API and integration patterns

Preferred Skills

• Experience implementing agentic development in Salesforce ecosystem
• Exposure to:
  • Agentforce / Salesforce AI / enterprise AI tools
  • CI/CD pipelines with AI automation
• Experience building:
  • Multi-agent workflows
  • Autonomous testing solutions

Roles & Responsibilities

1. Copilot Agent Development (Core Responsibility)
   • Design and build AI agents using GitHub Copilot to support:
     • Salesforce development (Apex, LWC, integrations)
     • Automated testing and QA workflows
   • Enable Copilot-driven code generation, refactoring, and debugging across SDLC
2. Salesforce Development Enablement
   • Leverage AI and Copilot to accelerate:
     • Apex / LWC development
     • API integrations and backend logic
     • Code modernization and enhancements
   • Convert design artifacts (e.g., Figma inputs where applicable) into code scaffolding and components (based on Copilot usage patterns observed in internal PoCs)
3. AI-Driven Testing & Automation
   • Build AI agents to automate:
     • Test case generation
     • Unit test creation and execution
     • Regression and functional testing
   • Use Copilot to improve test coverage, reduce manual effort, and enable TDD adoption
   • Support transition toward AI-assisted/autonomous testing pipelines
4. Prompt Engineering & Optimization
   • Design and optimize prompts using:
     • Few-shot, structured prompting techniques
   • Build prompt templates and reusable patterns for development and testing use cases
   • Continuously refine prompts for better accuracy and context relevance
5. Python & AI Integration
   • Develop backend services and automation scripts using Python
   • Integrate AI agents with:
     • Salesforce platforms
     • DevOps pipelines
     • APIs and enterprise applications
6. LLM & Agentic Frameworks
   • Implement solutions using LLMs (GPT, Claude, or similar)
   • Build AI workflows using:
     • RAG (Retrieval-Augmented Generation)
     • Frameworks like LangChain (or equivalent)
7. Collaboration & Delivery
   • Work closely with Salesforce teams, QA, and architects
   • Participate in sprint delivery with embedded AI workflows
   • Drive adoption of AI-led SDLC transformation