Verified Job
Engineering - Architecture
Principal Engineer - Agentic Engineering
Engineering - Architecture
#1922
Remote / WFH
Equifax
Job Description
Principal Engineer - Agentic Engineering (Equifax)
Role Overview
Lead the transformation of Equifax’s SDLC by evolving GitHub Copilot into a secure, autonomous agentic system. You will be the single-threaded owner for architecting context retrieval, action execution, and the Model Context Protocol (MCP) toolset.
Key Responsibilities
Architect the strategic roadmap for Copilot, treating it as a first-class internal product.
Design & Manage MCP tools to integrate Copilot with ServiceNow, Atlassian, DataDog, and GCP.
Engineer scalable context strategies, RAG frameworks, and complex prompt refinement.
Establish security postures, RBAC, and "human-in-the-loop" safeguards for AI actions.
Lead technical teams and define KPIs/SLAs for system performance and observability.
Required Qualifications
Experience: 7+ years in Software Engineering (Java, SpringBoot) and Cloud-Native (GCP/GKE).
AI/LLM: 3-5+ years building intelligent agent systems/LLM platforms; 3+ years GitHub Copilot expertise.
Tools: Expert in GitHub Actions, CI/CD, Terraform, and Kubernetes.
Specialized: Deep understanding of Model Context Protocol (MCP) and Event-Driven Architecture.
Work Schedule
Hybrid: 3 days/week in-office (Tuesday - Thursday) in Pune.
Pro Tip: If it still says it's too long, remove the "Key Responsibilities" section and just keep the "Overview" and "Qualifications" to ensure it fits the character limit.
Role Overview
Lead the transformation of Equifax’s SDLC by evolving GitHub Copilot into a secure, autonomous agentic system. You will be the single-threaded owner for architecting context retrieval, action execution, and the Model Context Protocol (MCP) toolset.
Key Responsibilities
Architect the strategic roadmap for Copilot, treating it as a first-class internal product.
Design & Manage MCP tools to integrate Copilot with ServiceNow, Atlassian, DataDog, and GCP.
Engineer scalable context strategies, RAG frameworks, and complex prompt refinement.
Establish security postures, RBAC, and "human-in-the-loop" safeguards for AI actions.
Lead technical teams and define KPIs/SLAs for system performance and observability.
Required Qualifications
Experience: 7+ years in Software Engineering (Java, SpringBoot) and Cloud-Native (GCP/GKE).
AI/LLM: 3-5+ years building intelligent agent systems/LLM platforms; 3+ years GitHub Copilot expertise.
Tools: Expert in GitHub Actions, CI/CD, Terraform, and Kubernetes.
Specialized: Deep understanding of Model Context Protocol (MCP) and Event-Driven Architecture.
Work Schedule
Hybrid: 3 days/week in-office (Tuesday - Thursday) in Pune.
Pro Tip: If it still says it's too long, remove the "Key Responsibilities" section and just keep the "Overview" and "Qualifications" to ensure it fits the character limit.
