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    Home/Jobs/Principal Engineer - Agentic Engineering

    Principal Engineer - Agentic Engineering

    Equifax

    Pune
    7+ years
    Today
    ₹23–44 LPA
    Full-time
    Hybrid

    Skills Required

    LLM
    Retrieval-Augmented Generation (RAG)
    Java
    Spring Boot
    TypeScript
    JavaScript
    HTML
    CSS
    GitHub Copilot
    GCP
    Kubernetes
    Microservices
    GitHub Actions
    Jenkins
    Terraform

    Description

    Equifax is seeking a visionary Principal Engineer to lead the charge in revolutionizing their product by embarking on a transformation journey. The goal is to create a highly leveraged engineering organization where GitHub Copilot acts as a true autonomous agent. The role requires being in the office 3 days/week on Tues - Thurs.

    Company: Equifax

    Role: Principal Engineer - Agentic Engineering

    Location: Pune, India (3 days/week in office on Tues - Thurs)

    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

    Key Skills:

    • Java
    • SpringBoot
    • TypeScript/JavaScript
    • HTML
    • CSS
    • GCP
    • Kubernetes
    • GitHub Copilot
    • GitHub Actions
    • Jenkins CI/CD pipelines
    • Terraform
    • Helm Charts
    • ServiceNow
    • Atlassian
    • DataDog
    • GCP SDKs
    • GKE
    • Python
    • Go
    • Node.js

    Qualification:

    • Bachelor's degree in Computer Science or equivalent experience

    Role Focus:

    • Define the strategic roadmap for the platform with GitHub Copilot
    • 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
    • Engineer the strategy for providing scalable context to GitHub Copilot
    • Design, test, and refine complex prompts and contextual data frameworks
    • Define and monitor key performance indicators (KPIs) for the agentic system's effectiveness
    • Establish the platform's security posture by implementing safeguards for custom tools and APIs exposed to Copilot
    • Define and enforce granular, code-driven permissions (RBAC) for the custom GitHub Actions and APIs that Copilot can invoke

    Additional responsibilities:

    • Build strong relationships with both internal and external stakeholders
    • Demonstrate excellent communication skills
    • Build and manage strong technical teams
    • Provide deep troubleshooting skills
    • Mentor, coach and develop junior and other engineers
    • Ensure compliance with EFX secure software development guidelines and best practices
    • Define, maintain and report SLA, SLO, SLIs meeting EFX engineering standards
    • Collaborate with architects, SRE leads and other technical leadership on strategic technical direction, guidelines, and best practices
    • Drive up-to-date technical documentation
    • Create and deliver technical presentations to internal and external technical and non-technical stakeholders

    Nice to have:

    • GitHub Ecosystem Mastery
    • Software Engineering Excellence
    • API and Integration Mastery
    • Cloud-Native Proficiency
    • Systems Thinking
    • Event-Driven Architecture
    • Applied LLM Expertise
    • Tool-Use and Function-Calling Paradigm
    • Retrieval-Augmented Generation (RAG) Expert
    • Pragmatic Agent Orchestration

    Other:

    • Hybrid work setting
    • Comprehensive compensation and healthcare packages
    • Attractive paid time off
    • Organizational growth potential through online learning platform with guided career tracks

    Prepare for this role

    Recommended resources to build the skills for this position. Sponsored.

    Generative AI with Large Language Models

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    Large Language Models: Application through Production

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    Production-focused LLM course covering deployment, monitoring, and scaling.

    Google Kubernetes Engine Specialization

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    Deploy and manage containerized AI applications at scale with GKE.

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