AI Engineer

EquifaxSt. Louis, MO
Hybrid

About The Position

Equifax is seeking a visionary AI engineer to lead their technology transformation initiative. This role involves leading a talented team in architecting and deploying cutting-edge, cloud-native solutions for a large enterprise. The engineer 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. This includes the ability to design, develop, and deploy AI agents in the Google Cloud Platform. The 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. The position is not just about coding, but also about being an architect, a mentor, and a key driver of the team's technical vision. The role requires being in the office 3 days/week on Tuesdays, Wednesdays, and Thursdays. This position does not offer immigration sponsorship (current or future) including F-1 STEM OPT extension support.

Requirements

  • Bachelor's degree or equivalent experience
  • 7+ years in software engineering, with a strong track record of technical leadership and shipping complex, scalable systems.
  • Experience in a dedicated AI/ML role, with hands-on experience in model integration, MLOps, and applying AI to solve business problems.
  • Direct experience architecting and building solutions with LangChain, LangGraph, or similar agentic AI frameworks.
  • 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: 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.

Nice To Haves

  • Strong expertise in Generative AI (GenAI), including hands-on experience with models like Gemini, ChatGPT, Claude, or Llama.
  • 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.
  • A history of tackling ambiguous, complex technical challenges and architecting elegant, effective solutions.
  • Passionate about the potential of AI, but grounded in the practical realities of building and shipping reliable, production-ready software.
  • Thrive in a team-oriented environment, capable of mentoring other engineers and clearly communicating complex technical ideas to any audience.
  • Motivated by the opportunity to apply cutting-edge technology to solve meaningful, real-world problems at a massive scale.

Responsibilities

  • Implement Sophisticated AI Agents: Design, build, and deploy complex AI agents using LangChain and LangGraph. 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 AI agents perform with maximum accuracy, efficiency, and reliability.
  • Lead AI Research & Innovation: Stay at the bleeding edge of AI. Identify, prototype, and integrate the latest foundational models, RAG techniques, and agentic frameworks to solve unique business challenges.
  • Build for Production Scale on GCP: Engineer and operate AI systems in a scalable, reliable production environment on Google Cloud Platform.
  • Champion MLOps for Agentic Systems: Establish and lead best practices for the reliability, versioning, monitoring, and observability of 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 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 an 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.

Benefits

  • Comprehensive compensation and healthcare packages
  • 401k matching
  • Paid time off
  • Organizational growth potential through our online learning platform with guided career tracks
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