Lead AI Engineer

Role Overview: As a visionary AI engineer at Equifax, you will lead the technology transformation initiative by architecting and deploying cutting-edge, cloud-native solutions for a large enterprise. You will be at the forefront of modern development, utilizing AI-powered coding assistants and accelerating innovation to build highly scalable, reliable, and performant APIs, microservices, and PaaS/SaaS platforms. Your role will require a deep understanding of front-end and back-end technologies, cloud infrastructure, containerization, microservices architecture, and the agentic AI framework. You will not only be a coder but also an architect, mentor, and a key driver of the team's technical vision. Key Responsibilities: - Design, build, and deploy complex AI agents using LangChain and LangGraph to automate intricate decision-making within the claims lifecycle. - Develop and refine complex prompts and contextual data frameworks to ensure maximum accuracy, efficiency, and reliability of AI agents. - Stay updated on the latest AI advancements to identify, prototype, and integrate foundational models, RAG techniques, and agentic frameworks for solving unique business challenges. - Engineer and operate AI systems in a scalable, reliable production environment on Google Cloud Platform impacting millions of users. - Establish best practices for reliability, versioning, monitoring, and observability of AI agents using tools like Langfuse. - Collaborate with product leaders, data scientists, and engineers to translate business needs into innovative and effective technical solutions. - Utilize AI code-assist tools to accelerate development cycles, improve code quality, and drive continuous improvement. - Lead a cross-functional team of engineers, fostering a culture of technical excellence and mentorship. - Define key engineering metrics and ensure compliance with security, quality, and financial operations best practices. - Collaborate with stakeholders to define technical strategy, create software roadmaps, and make key architectural decisions. - Lead troubleshooting efforts to resolve production and customer issues effectively. - Drive technical documentation and deliver presentations to internal and external stakeholders. Qualifications Required: - Bachelor's degree or equivalent experience. - 7+ years of software engineering experience with a track record of technical leadership. - 2+ years in a dedicated AI/ML role with hands-on experience in model integration and MLOps. - 1+ years of experience in architecting solutions with agentic AI frameworks like LangChain or LangGraph. - Proficiency in Python, JavaScript/TypeScript, Java, and a modern front-end framework. - Hands-on experience with Google Cloud Platform, Kubernetes, and observability tools. - Strong database knowledge in SQL and NoSQL databases. - Familiarity with cloud platforms, containerization, IaC, CI/CD tools, and modern development practices. (Note: Additional details about the company were not provided in the job description.) Role Overview: As a visionary AI engineer at Equifax, you will lead the technology transformation initiative by architecting and deploying cutting-edge, cloud-native solutions for a large enterprise. You will be at the forefront of modern development, utilizing AI-powered coding assistants and accelerating innovation to build highly scalable, reliable, and performant APIs, microservices, and PaaS/SaaS platforms. Your role will require a deep understanding of front-end and back-end technologies, cloud infrastructure, containerization, microservices architecture, and the agentic AI framework. You will not only be a coder but also an architect, mentor, and a key driver of the team's technical vision. Key Responsibilities: - Design, build, and deploy complex AI agents using LangChain and LangGraph to automate intricate decision-making within the claims lifecycle. - Develop and refine complex prompts and contextual data frameworks to ensure maximum accuracy, efficiency, and reliability of AI agents. - Stay updated on the latest AI advancements to identify, prototype, and integrate foundational models, RAG techniques, and agentic frameworks for solving unique business challenges. - Engineer and operate AI systems in a scalable, reliable production environment on Google Cloud Platform impacting millions of users. - Establish best practices for reliability, versioning, monitoring, and observability of AI agents using tools like Langfuse. - Collaborate with product leaders, data scientists, and engineers to translate business needs into innovative and effective technical solutions. - Utilize AI code-assist tools to accelerate development cycles, improve code quality, and drive continuous improvement. - Lead a cross-functional team of engineers, fostering a culture of technical excellence and mentorship. - Define key engineering metrics and ensure compliance with security, quality, and financial operations best practices. - Collab