Explicitly requires vibe coding skills—uses AI code assistants (GitHub Copilot, Gemini, Claude) and agentic AI frameworks for rapid development and prototyping.
About the Role
Equifax is hiring an AI Engineer to lead design and delivery of cloud-native, production-scale AI systems and agentic workflows on Google Cloud Platform. The role combines hands-on development (Python/JS/Java), MLOps, prompt and context engineering, and technical leadership for a hybrid team working in-office three days per week.
Job Description
Role
Equifax is seeking an AI Engineer to lead architecture, development, and deployment of enterprise-grade, cloud-native AI solutions and agentic systems. The role combines technical leadership, hands-on engineering, and team mentoring to deliver scalable APIs, microservices, and AI agents in production on Google Cloud Platform.
Key Responsibilities
- Design, build, and deploy complex AI agents using LangChain and LangGraph.
- Lead prompt and context engineering to optimize agent performance and reliability.
- Research and prototype foundational models, RAG techniques, and agentic frameworks.
- Build for production scale on Google Cloud Platform (GCP) and Vertex AI.
- Establish MLOps best practices for reliability, versioning, monitoring, and observability (e.g., using Langfuse).
- Use AI code-assist tools (GitHub Copilot, Gemini, Claude) to accelerate development, documentation, testing, and monitoring.
- Build, manage, and mentor a cross-functional team of software, quality, and reliability engineers.
- Define and report engineering metrics (SLA, SLO, SLI) and ensure DevSecOps and FinOps practices.
- Collaborate with product managers, architects, SREs, and business partners to set technical strategy and roadmaps.
- Lead troubleshooting, incident resolution, and agile ceremonies (Sprint Planning, Retrospectives).
- Maintain technical documentation, run books, and deliver technical presentations to varied audiences.
Requirements
- Bachelor’s degree or equivalent experience.
- 7+ years in software engineering with proven technical leadership and delivery of complex, scalable systems.
- Hands-on AI/ML experience: model integration, MLOps, and applying AI to business problems.
- Direct experience with agentic AI frameworks (LangChain, LangGraph) and deploying AI agents to production.
- Experience operating AI systems on Google Cloud Platform and Vertex AI.
- 3+ years working with Kubernetes workloads; mastery of Docker.
- Proficiency in Python and 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.
- Infrastructure-as-Code experience (Terraform or CloudFormation) and CI/CD tooling (Github Actions, Argo CD, Jenkins).
- Database experience with SQL (Spanned DB, Alloy DB, PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB, Firestore).
- Strong system design, cloud architecture, DevSecOps, FinOps, monitoring/observability, and troubleshooting skills.
Nice-to-have / What Could Set You Apart
- Strong Generative AI experience (Gemini, ChatGPT, Claude, Llama).
- Extensive experience deploying agentic AI to production and leveraging AI-powered developer tools.
- Proven ability to solve ambiguous, complex technical challenges and mentor engineering teams.
Location & Work Arrangement
- Role is hybrid: requires being in the office 3 days/week (Tues–Thurs). Locations listed: St. Louis / Alpharetta, United States.
- This position does not provide immigration sponsorship or F-1 STEM OPT extension support.
Benefits (summary)
- Comprehensive compensation and healthcare packages
- 401(k) matching
- Paid time off
- Organizational growth potential and online learning platform with guided career tracks