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Equifax · 3 hours ago

AI Engineer

St Louis, MO

Full-time

Hybrid

Senior Level

7+ years exp

Equifax is seeking a visionary AI engineer to lead their 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, focusing on modern development practices and AI-powered solutions.

AnalyticsConsultingDatabase

No H1B

Responsibilities

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

Qualification

AI/ML experienceGoogle Cloud PlatformLangChain/LangGraphMLOpsPythonKubernetesDockerCI/CD toolsSQL/NoSQL databasesAgile methodologiesTechnical leadershipProblem-solvingMentoringTechnical documentation

Required

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

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

Mastery of Docker for containerizing applications and Kubernetes for orchestration

Proficiency with tools like Terraform or CloudFormation to manage infrastructure programmatically

Experience with CI/CD tools such as Github Actions, Argo CD, Jenkins

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

Preferred

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