Job Description :

Equifax is seeking a visionary AI engineer to lead our technology transformation initiative.

In this role, you will lead a talented team in architecting and deploying cutting-edge, cloud-native solutions for a large enterprise.

You will be at the forefront of modern development, employing vibe coding concepts with AI-powered coding assistants like GitHub Copilot, Gemini, and accelerate innovation and build highly scalable, reliable, and performant APIs, microservices, and PaaS/SaaS platforms, including the ability to design, develop, and deploy AI agents in the google cloud platform.

This role requires a deep understanding of both front-end and back-end technologies, combined with mastery of cloud infrastructure, containerization, microservices architecture and the agentic AI framework.

You're not just a coder; you're an architect, a mentor, and a key driver of the team's technical vision.

If you are passionate about solving complex problems and mentoring a high-performing team, we want to hear from you.

What You'll Do :

As our Senior AI Engineer, you will be the driving force behind our technical vision and execution.

Your core responsibilities include :

- Implement Sophisticated AI Agents : Design, build, and deploy complex AI agents using LangChain and LangGraph.

- You will own the core logic that automates intricate decision-making within the claims lifecycle.

- Master Prompt & Context Engineering : Design, test, and refine complex prompts and contextual data frameworks to ensure our AI agents perform with maximum accuracy, efficiency, and reliability.

- Lead AI Research & Innovation : Stay at the bleeding edge of AI.

- You'll be responsible for identifying, prototyping, and integrating the latest foundational models, RAG techniques, and agentic frameworks to solve unique business challenges.

- Build for Production Scale on GCP : Engineer and operate our AI systems in a scalable, reliable production environment on Google Cloud Platform.

- Your work will directly impact millions of users.

- Champion MLOps for Agentic Systems : Establish and lead best practices for the reliability, versioning, monitoring, and observability of our AI agents, using tools like Langfuse to ensure production-grade performance.

- Collaborate to Deliver Impact : Partner closely with product leaders, data scientists, and other engineers to translate business needs into technical reality, ensuring our AI solutions are both innovative and effective.

- Champion modern software development practices by actively using AI code-assist tools (e.g., Gemini code assists, Github Copilot, Claude code) to accelerate development cycles, generate documentation, improve code quality, testing, and monitoring & observability practices.

- Build, manage, and mentor a cross-functional team of software, quality, and reliability engineers, fostering a culture of technical excellence and continuous improvement.

- Define and report on key engineering metrics (SLA, SLO, SLI) and ensure compliance with security, quality, and financial operations (DevSecOps, FinOps) best practices.

- Collaborate with product managers, architects, SREs and business partners to define technical strategy, create software roadmaps, and make key architectural and design decisions.

- Lead troubleshooting efforts to resolve production and customer issues, demonstrating deep technical expertise and problem-solving skills.

- Participate and lead agile team activities, including Sprint Planning and Retrospectives, to ensure efficient and predictable delivery.

- Lead with a data/metrics driven mindset with a extreme focus towards optimizing and creating efficient solutions.

- Drive up-to-date technical documentation including support, end user documentation and run books.

- 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.

What You'll Bring (Experience & Technical Stack) :

- Bachelor's degree or equivalent experience.

- 5+ years in software engineering, with a strong track record of technical leadership and shipping complex, scalable systems.

- 2+ years in a dedicated AI/ML role, with hands-on experience in model integration, MLOps, and applying AI to solve business problems.

- 1+ years of direct experience architecting and building solutions with LangChain, LangGraph, or similar agentic AI frameworks.

- 2+ years of in-depth experience with Google Cloud Platform (GCP), specifically its AI/ML services (Vertex AI, etc.).

- 3+ years of proven experience leveraging Kubernetes workloads.

- Proficiency in Python, JavaScript/TypeScript and/or Java and working knowledge of a modern front-end framework (Angular, React, or Vue) to collaborate effectively with UI teams.

- Hands-on experience with LLM observability tools like Langfuse for monitoring and debugging agentic workflows.

Cloud-Native Proficiency :

- Cloud Platforms : Extensive hands-on experience with at least one major cloud provider (AWS, Google Cloud, or Azure).

- Containerization : Mastery of Docker for containerizing applications and Kubernetes for orchestration.

- Infrastructure as Code (IaC) : Proficiency with tools like Terraform or CloudFormation to manage infrastructure programmatically.

- CI/CD Tools : Experience with CI/CD tools such as Github Actions, Argo CD, Jenkins.

- Database Knowledge : Strong experience with both SQL (e.g., Spanned DB, Alloy DB, PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, DynamoDB and Firestore) databases.

What Could Set You Apart :

- Strong expertise in Generative AI (GenAI), including hands-on experience with models like Gemini, ChatGPT, Claude, or Llama.

- You are adept at leveraging modern development tools, including AI-powered code assistants (like GitHub Copilot), to accelerate the development lifecycle and rapidly ship high-quality features.

- Experience creating and deploying AI agents to production environments.

- You have a history of tackling ambiguous, complex technical challenges and architecting elegant, effective solutions.

- You are passionate about the potential of AI, but you are grounded in the practical realities of building and shipping reliable, production-ready software.

- You thrive in a team-oriented environment, capable of mentoring other engineers and clearly communicating complex technical ideas to any audience.

- You are motivated by the opportunity to apply cutting-edge technology to solve meaningful, real-world problems at a massive scale.