Equifax
Equifax is seeking a visionary AI engineer to lead our 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. You will be at the forefront of modern development, employing cutting‑edge AI‑powered coding assistants like GitHub Copilot, Gemini, and accelerate innovation to build highly scalable, reliable, and performant APIs, microservices, and PaaS/SaaS platforms, including the ability to design, develop, and deploy AI agents in Google Cloud Platform. This 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. You're not just a coder; you're an architect, a mentor, and a key driver of the team's technical vision. If you are passionate about solving complex problems and mentoring a high‑performing team, we want to hear from you.
This role requires being in the office 3 days/week on Tues - Thurs.
This position does not offer immigration sponsorship (current or future) including F-1 STEM OPT extension support.
What You’ll Do
Implement sophisticated AI agents: Design, build, and deploy complex AI agents using LangChain and LangGraph, owning 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, 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 our AI systems in a scalable, reliable production environment on Google Cloud Platform, directly impacting millions of users.
Champion MLOps for agentic systems: Establish best practices for 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 engineers to translate business needs into technical reality.
Champion modern software development practices by actively using AI code‑assist tools 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 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, focusing on 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 stakeholders, communicating with clarity and precision.
What You'll Bring (Experience & Technical Stack)
Bachelor's degree or equivalent experience.
7+ years in software engineering, with a strong track record of technical leadership and shipping complex, scalable systems.
2+ years in a dedicated AI/ML role, with hands‑on experience in model integration, MLOps, and applying AI to solve business problems.
1+ years of direct experience architecting and building solutions with LangChain, LangGraph, or similar agentic AI frameworks.
2+ years of 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).
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).
Mastery of Docker for containerizing applications and Kubernetes for orchestration.
Proficiency with IaC tools such as Terraform or CloudFormation.
Experience with CI/CD tools such as GitHub Actions, Argo CD, or Jenkins.
Strong experience with SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB, Firestore) databases.
What could set you apart
Strong expertise in Generative AI (GenAI), including hands‑on experience with models like Gemini, ChatGPT, Claude, or Llama.
Proficiency in leveraging modern development tools, including AI‑powered code assistants, to accelerate the development lifecycle.
Experience creating and deploying AI agents to production environments.
History of tackling ambiguous, complex technical challenges and architecting elegant, effective solutions.
Passion for the potential of AI, grounded in practical realities of building and shipping reliable, production‑ready software.
Thriving in a team‑oriented environment, capable of mentoring other engineers and clearly communicating complex technical ideas.
Motivation to apply cutting‑edge technology to solve meaningful, real‑world problems at a massive scale.
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This role requires being in the office 3 days/week on Tues - Thurs.
This position does not offer immigration sponsorship (current or future) including F-1 STEM OPT extension support.
What You’ll Do
Implement sophisticated AI agents: Design, build, and deploy complex AI agents using LangChain and LangGraph, owning 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, 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 our AI systems in a scalable, reliable production environment on Google Cloud Platform, directly impacting millions of users.
Champion MLOps for agentic systems: Establish best practices for 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 engineers to translate business needs into technical reality.
Champion modern software development practices by actively using AI code‑assist tools 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 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, focusing on 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 stakeholders, communicating with clarity and precision.
What You'll Bring (Experience & Technical Stack)
Bachelor's degree or equivalent experience.
7+ years in software engineering, with a strong track record of technical leadership and shipping complex, scalable systems.
2+ years in a dedicated AI/ML role, with hands‑on experience in model integration, MLOps, and applying AI to solve business problems.
1+ years of direct experience architecting and building solutions with LangChain, LangGraph, or similar agentic AI frameworks.
2+ years of 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).
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).
Mastery of Docker for containerizing applications and Kubernetes for orchestration.
Proficiency with IaC tools such as Terraform or CloudFormation.
Experience with CI/CD tools such as GitHub Actions, Argo CD, or Jenkins.
Strong experience with SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB, Firestore) databases.
What could set you apart
Strong expertise in Generative AI (GenAI), including hands‑on experience with models like Gemini, ChatGPT, Claude, or Llama.
Proficiency in leveraging modern development tools, including AI‑powered code assistants, to accelerate the development lifecycle.
Experience creating and deploying AI agents to production environments.
History of tackling ambiguous, complex technical challenges and architecting elegant, effective solutions.
Passion for the potential of AI, grounded in practical realities of building and shipping reliable, production‑ready software.
Thriving in a team‑oriented environment, capable of mentoring other engineers and clearly communicating complex technical ideas.
Motivation to apply cutting‑edge technology to solve meaningful, real‑world problems at a massive scale.
#J-18808-Ljbffr