Apply on Employer Site

Equifax · 3 days ago

Principal Engineer, Agentic Engineering

St Louis, MO

Full-time

Hybrid

Senior Level, Lead/Staff

7+ years exp

Equifax is seeking a visionary Principal Engineer to lead the charge in revolutionizing their product through a transformation journey. The role involves owning and transforming the software development lifecycle by leveraging GitHub Copilot to create a highly leveraged engineering organization, ensuring efficient performance and security. Responsibilities include defining strategic roadmaps, managing tools for interaction with third-party services, and optimizing the agentic system's effectiveness.

AnalyticsConsultingDatabase

No H1B

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

Qualification

GitHub Copilot expertiseCloud-native solutionsMicroservices architectureFull stack developmentJava programmingGCP proficiencyAPI designCI/CD pipelinesTroubleshooting skillsSystems thinkingCommunication skillsTeam management

Required

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, SpringBoot, TypeScript/JavaScript, HTML, CSS

7+ years experience designing and developing cloud-native solutions

7+ years experience designing and developing microservices using Java, SpringBoot, GCP SDKs, GKE/Kubernetes

3+ years of github copilot experience, preferably an expert

3-5+ years of 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

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