INTRODUCTION

Equifax is seeking a visionary Principal Engineer to lead the charge in revolutionizing our product embarking on a transformation journey. You will be the single-threaded owner responsible for transforming our software development lifecycle (SDLC) by orchestrating and extending the capabilities of GitHub Copilot. The ultimate goal is to create a highly leveraged engineering organization where Copilot acts as a true autonomous agent, handling complex tasks from code generation and testing to incident response and documentation, all while operating within a well-defined, observable, and secure framework you own.

ROLE AND RESPONSIBILITIES

• Define the strategic roadmap for the platform with GitHub Copilot, treating it as a first-class internal product. Architect the complete system for Copilot's invocation, context retrieval, and action execution using custom tools.
• Design and manage the Model Context Protocol (MCP) toolset, enabling Copilot's interaction with third-party services like ServiceNow, Atlassian, DataDog, and GCP for context and action.
• Engineer the strategy for providing scalable context to GitHub Copilot, shaping its persona and behavior by translating internal engineering standards into a centralized, version-controlled repository of custom instructions and integrating vendor-provided connectors for various contexts.
• Design, test, and refine complex prompts and contextual data frameworks to ensure our coding agents perform with maximum accuracy, efficiency, and reliability.
• Define and monitor key performance indicators (KPIs) for the agentic system's effectiveness and implement a robust observability stack to track Copilot's interactions for continuous optimization.
• Establish the platform's security posture by implementing safeguards for custom tools and APIs exposed to Copilot, and design a "human-in-the-loop" framework for critical actions.
• Define and enforce granular, code-driven permissions (RBAC) for the custom GitHub Actions and APIs that Copilot can invoke, ensuring the principle of least privilege.
• Demonstrate a deep understanding of cloud native, distributed micro service based architectures.
• Deliver solutions for complex business problems through software standard SDLC.
• Build strong relationships with both internal and external stakeholders including product, business and sales partners.
• Demonstrate excellent communication skills with the ability to both simplify complex problems and also dive deeper if needed.
• Build and manage strong technical teams that deliver complex software solutions that scale.
• Provide deep troubleshooting skills with the ability to lead and solve production and customer issues under pressure.
• Leverage strong experience in full stack software development and public cloud like GCP and AWS.
• Mentor, coach and develop junior and other engineers.
• Lead with a data/metrics driven mindset with extreme focus towards optimizing and creating efficient solutions.
• Ensure compliance with EFX secure software development guidelines and best practices and responsible for meeting and maintaining QE, DevSec, and FinOps KPIs.
• Define, maintain and report SLA, SLO, SLIs meeting EFX engineering standards in partnership with the product, engineering and architecture teams.
• Collaborate with architects, SRE leads and other technical leadership on strategic technical direction, guidelines, and best practices.
• Drive up-to-date technical documentation including support, end user documentation and run books.
• Responsible for implementation architecture decision making associated with Product features/stories, refactoring work, and EOSL decisions.
• Create and deliver technical presentations to internal and external technical and non-technical stakeholders communicating with clarity and precision, and present complex information in a concise format that is audience appropriate.

BASIC QUALIFICATIONS

• Bachelor's degree in Computer Science or equivalent experience.
• 7+ years of hands on software engineering experience.
• 7+ years experience writing, debugging, and troubleshooting code in mainstream Java, Python, Go SpringBoot, TypeScript/JavaScript, HTML, CSS or similar languages.
• 1+ years of AI-powered coding assistant experience, preferably Github Copilot.
• Experience designing and developing cloud-native solutions.
• Experience designing and developing microservices using Java, SpringBoot, GCP SDKs, GKE/Kubernetes.
• Hands-on experience in building and architecting intelligent agent systems or platforms that integrate with LLMs.
• Hands on experience deploying and releasing software using Github actions, Jenkins CI/CD pipelines, understand infrastructure-as-code concepts, Helm Charts, and Terraform constructs.

PREFERRED QUALIFICATIONS

• GitHub Ecosystem Mastery: Deep, hands-on expertise with the full GitHub platform, including GitHub Actions, GitHub Apps, webhooks, and the REST/GraphQL APIs.
• Software Engineering Excellence: Senior-level proficiency in a language like Python, Go, or Node.js, with a deep understanding of software architecture and building scalable, maintainable services.
• API and Integration Mastery: Demonstrable experience designing and consuming RESTful APIs and securely integrating disparate SaaS systems. Deep familiarity with the Model Context Protocol (MCP) and experience defining services that conform to its specification is a strong requirement.
• Cloud-Native Proficiency: Deep familiarity with Google Cloud Platform (GCP), including Kubernetes, and IAM.
• Systems Thinking: The ability to see the entire SDLC as an interconnected system and reason about how to inject Copilot for maximum leverage.
• Event-Driven Architecture: Experience building systems that react to events, especially GitHub webhook events.
• Applied LLM Expertise: Hands-on experience building applications that integrate with Large Language Models (LLMs), with a focus on practical application.
• Tool-Use and Function-Calling Paradigm: A deep understanding of how to build and expose "tools" (APIs, functions, custom actions) for an LLM agent to consume.
• Retrieval-Augmented Generation (RAG) Expert: Practical knowledge of designing, implementing, and optimizing RAG systems.
• Pragmatic Agent Orchestration: The ability to orchestrate workflows around a pre-existing, powerful agent like Copilot.

LI-ES1

LI-Hybrid