AI Engineer

Role

Equifax is hiring a senior AI Engineer to lead architecture and delivery of cloud-native, agentic AI solutions for large-scale enterprise use. The role focuses on designing, building, and operating AI agents, scalable APIs and microservices, and production-grade MLOps on Google Cloud while mentoring a cross-functional engineering team.

Key Responsibilities

• Design, implement, and deploy complex AI agents using LangChain and LangGraph.
• Lead prompt and context engineering to maximize agent accuracy and reliability.
• Research, prototype, and integrate foundational models, RAG techniques, and agentic frameworks.
• Build, operate, and scale AI systems in production on Google Cloud Platform (GCP), including Vertex AI services.
• Establish MLOps best practices for reliability, versioning, monitoring, and observability (e.g., using Langfuse).
• Use AI-powered code-assist tools (e.g., Gemini code assists, GitHub Copilot, Claude code) to accelerate development, documentation, testing, and monitoring.
• Define and report on engineering metrics (SLA, SLO, SLI) and enforce DevSecOps and FinOps practices.
• Lead troubleshooting and incident response to resolve production and customer issues.
• Manage and mentor a cross-functional team of software, quality, and reliability engineers.
• Participate in and lead Agile ceremonies (Sprint Planning, Retrospectives) and deliver technical presentations and documentation.

Requirements

• Bachelor’s degree or equivalent experience.
• 7+ years in software engineering with a track record of technical leadership and shipping scalable systems.
• Hands-on experience in an AI/ML role, including model integration and MLOps.
• Direct experience with LangChain, LangGraph, or similar agentic AI frameworks.
• In-depth experience with Google Cloud Platform and AI/ML services (e.g., Vertex AI).
• 3+ years working with Kubernetes workloads.
• Proficiency in Python, JavaScript/TypeScript, and/or Java; working knowledge of a modern front-end framework (Angular, React, or Vue).
• Experience with LLM observability tools such as Langfuse.

Cloud-native and Infrastructure

• Hands-on experience with at least one major cloud provider (AWS, Google Cloud, or Azure).
• Containerization with Docker and orchestration with Kubernetes.
• Infrastructure as Code using tools like Terraform or CloudFormation.
• CI/CD tools such as GitHub Actions, Argo CD, or Jenkins.
• Database experience with SQL (Spanned DB, Alloy DB, PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB, Firestore).

Nice to Have / Differentiators

• Strong expertise in Generative AI (Gemini, ChatGPT, Claude, Llama) and experience deploying GenAI to production.
• Proven experience creating and shipping AI agents in production.
• History of solving ambiguous technical challenges and communicating complex ideas to varied audiences.

Workplace & Sponsorship

• Hybrid role: required in-office presence 3 days per week (Tuesday–Thursday).
• This position does not provide immigration sponsorship (including F-1 STEM OPT).