Senior AI Engineer
Explicitly requires vibe coding skills and use of AI code assistants (GitHub Copilot, Gemini, Claude) to accelerate development and build agentic AI systems.
About the Role
Lead the design, development, and production deployment of cloud-native AI solutions and agentic systems at enterprise scale on Google Cloud. Drive architecture, implement AI agents and prompt/context engineering, use AI code assistants to accelerate delivery, and mentor engineering teams to build scalable, reliable APIs and platforms.
Job Description
Role
Equifax is hiring a Senior AI Engineer to design, build, and operate cloud-native AI systems and agentic AI solutions at production scale on Google Cloud Platform. The role focuses on developing AI agents, integrating foundational models, and delivering highly scalable, reliable APIs, microservices, and PaaS/SaaS platforms while mentoring engineers and collaborating with product and data teams.
Key Responsibilities
- Design, build, and deploy complex AI agents using LangChain and LangGraph to automate decision-making within business workflows.
- Lead prompt and context engineering efforts to maximize accuracy, efficiency, and reliability of AI agents.
- Research, prototype, and integrate foundational models, RAG techniques, and agentic frameworks to address business problems.
- Engineer and operate scalable, reliable production systems on Google Cloud Platform (GCP), impacting large user bases.
- Use AI code-assist tools (e.g., Gemini code assists, Github Copilot, Claude code) to accelerate development, improve code quality, and generate documentation.
- Define and report on engineering metrics (SLA, SLO, SLI) and enforce DevSecOps and FinOps best practices.
- Lead troubleshooting for production incidents and participate in agile team activities (Sprint Planning, Retrospectives).
- Drive technical documentation, runbooks, and support materials.
Requirements
- Bachelor’s degree or equivalent experience.
- 5+ years of software engineering experience and 5+ years writing, debugging, and troubleshooting code.
- 2+ years in a dedicated AI/ML role with hands-on model integration and MLOps experience.
- 1+ years architecting and building solutions with LangChain, LangGraph, or similar agentic AI frameworks.
- 2+ years of experience with Google Cloud Platform (GCP), including AI/ML services such as Vertex AI.
- 3+ years working with Kubernetes workloads.
- Proficiency in Python, JavaScript/TypeScript, and/or Java, plus working knowledge of a modern front-end framework (Angular, React, or Vue).
- Hands-on experience with LLM observability tools like Langfuse.
Cloud-native & Infrastructure
- Experience with major cloud providers (AWS, Google Cloud, or Azure).
- Containerization with Docker and orchestration with Kubernetes.
- Infrastructure-as-Code tools such as Terraform or CloudFormation.
- CI/CD experience with tools like Github Actions, Argo CD, or Jenkins.
- Database experience with SQL (Spanned DB, Alloy DB, PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB, Firestore).
What Could Set You Apart
- Strong Generative AI (GenAI) expertise and hands-on experience with models like Gemini, ChatGPT, Claude, or Llama.
- Proven experience creating and deploying AI agents to production.
- Demonstrated ability to tackle ambiguous, complex technical challenges and deliver production-ready solutions.
- Experience leveraging AI-powered coding assistants to accelerate development and ship high-quality features.
- Strong communication, mentoring, and team collaboration skills.