Based in Dublin, Leinster, Ireland, Experian is a global information services company that operates in 40 countries around the world and has additional headquarters in the United K
Senior AI Engineer – AI & Credit Analytics
Location
United States
Posted
1 day ago
Salary
$133.1K - $239.6K / year
Seniority
Senior
Job Description
Senior AI Engineer – AI & Credit Analytics
Experian
• Build scalable, production-grade AI systems that automate and enhance credit analytics and credit decisioning workflows • Develop and integrate AI solutions across the credit lifecycle, including origination, underwriting, limit setting, portfolio monitoring, and model validation • Develop evaluation and guardrail frameworks to ensure response accuracy, reduce hallucinations, and support human-in-the-loop review, including offline testing with ground-truth datasets • Develop and operate enterprise-grade AI services with a focus on scalability, security, reliability, performance, and latency optimization • Implement LLMOps and GenAI operational practices, including prompt management, model versioning, monitoring, CI/CD pipelines, and observability for cost, latency, and response quality • Partner with analytics, engineering, and product teams to embed AI into existing platforms and deliver new AI-driven capabilities across the organization • Evaluate and adopt modern orchestration frameworks and cloud-native AI tools (such as LangGraph and AWS-based services), while staying current with new AI system design patterns
Job Requirements
- Master's degree in Computer Science, Data Science, or a related quantitative field, or equivalent practical experience
- 8+ years of professional experience in data science, machine learning, or AI engineering to build and operate production-grade AI, ML, or Generative AI systems
- Domain experience in financial services, with exposure to credit, lending, risk, or analytics-driven decisioning environments
- Experience working in regulated or governed environments, with understanding of data governance, model risk management, regulatory compliance, and responsible AI practices
- Hands-on experience developing Generative AI and LLM-based applications, including retrieval-augmented generation (RAG), prompt design, evaluation methods, and system optimization in production environments
- Proficiency in Python (required) and SQL
- Familiarity with modern Generative AI frameworks
Benefits
- Great compensation package and bonus plan
- Core benefits including medical, dental, vision, and matching 401K
- Flexible work environment, ability to work remote, hybrid or in-office
- Flexible time off including volunteer time off, vacation, sick and 12-paid holidays
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Role Description Insurance is one of the world's largest industries and one of the most painful to interact with. Paper forms. Sluggish call centres. Three-week underwriting cycles. Claims that vanish into queues. We are rebuilding all of it on top of a modern platform and AI agents that actually do the work, not pretend to. You will not be picking up tickets. You will be deciding what to build, prototyping it on Monday, shipping a draft to a real customer by Friday, and improving it from real usage. We expect you to push the product, the codebase, and the way we work. We are looking for someone who treats AI as a creative material, not a feature on a roadmap. The next year of insurance is being defined right now. What gets automated, what gets reimagined, what gets thrown out. We want builders who want to be in that room and ship the answer. The team is small. The mandate is large. If your highest-energy work has historically come from solving real problems end to end, this is the seat. What You Will Do - Own outcomes, not tickets. Pick the biggest lever for our customers each sprint and drive it to live. Surface the next one yourself. - Build with AI as a primary tool, not a chatbot bolt-on. OCR, document understanding, generation, agent loops, evaluation harnesses. You decide where each fits. - Ship prototypes fast, then make them production-grade. A working demo on day three beats a perfect plan on day ten. - Work directly with customers. You will see real claims, real underwriting screens, real broker workflows. You will watch users hit dead ends and decide what to fix. - Raise the bar on the codebase. Reviews, refactors, testability, observability. Not as policy, as habit. - Push the team forward. Skills, agents, internal tools, engineering standards. Propose them, build them, get them adopted. Who You Are - You ship. Ideas without execution do not count for you. - High agency. You do not wait for a card to be assigned. You see what is worth doing and you start. - Strong opinions, loosely held. You make calls with incomplete information and change your mind when the evidence shifts. - Curious about the domain. Insurance is messy and full of weird incentives. That intrigues you, not annoys you. - Fluent with AI. You have shipped something real with LLMs or agents. You know where the magic ends and where you have to engineer carefully. - Care about humans on the other end. Insurance done right gives people peace of mind in their worst weeks. That is the point. Your Toolbox - Node.js + TypeScript + Nest.js on the back end - Vue (and some React) on the front end - GraphQL, MongoDB, Docker, AWS - AI work spans OpenAI, Anthropic, Google, plus a growing set of in-house skills and agents - You do not need to have used every piece. You do need to be the kind of engineer who picks up a new tool and is shipping with it within the week. What We Expect at This Level - 6+ years building production systems. Track record of complex, customer-facing software shipped, not just maintained. - Real AI experience. You have built and shipped at least one substantive AI-driven feature. POCs that died in a notebook do not count here. - Strong fundamentals. OO, design patterns, testing, web security, performance. You do not need a refresher. - Cloud comfort. AWS, Azure, or GCP. At least one in depth, the rest enough to hold a conversation. - Communication. You can explain a tradeoff to a non-technical stakeholder in two minutes and to an engineer in one. Not Suitable for the Role If… - You prefer tickets assigned to you over choosing what to build. - You measure your work in lines of code, not outcomes. - You see AI as a buzzword to put on your CV rather than a tool you have actually used in anger. - You want a process-heavy environment with detailed specs handed down from product. - You are looking for a maintenance role on a finished platform. Why CoverGo Insurance is the rare industry where AI can save people hours of their worst weeks. We are already shipping AI-powered claims, underwriting, distribution, and document automation to enterprise carriers across five continents. The platform is real. The customers are real. The next chapter is yours to help write. Why You'll Love Working Here - 100% Remote Work - 15 Days of Annual Leave - Annual Performance Bonus - Remote Work Allowance - Anniversary Bonus - Health Insurance - Company Activities and Events - Learning and Development Plan By submitting your application, you confirm that you have read, understood, and accepted the content of CoverGo’s Privacy Notice and you consent to the processing of your data as part of this application.
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• Go to the field: talk to users, shadow their workflows, capture the as‑is → goals & constraints. • Define hypotheses & KPIs (precision/recall, FPR, TAT, coverage, cost/decision) and turn them into experiment plans. • Design decision flows that mix LLMs, retrieval/RAG, classical ML, and lightweight rules; ensure explainability and auditability. • Build quick prototypes (notebook → lightweight service/API) and measure their impact on real data. • Create evaluation sets and scoring rubrics (offline + side‑by‑side + sanity checks + guardrails). • Present findings & recommendations directly to decision‑makers; propose rollout (pilot → production‑lite → scale). • Lead innovation processes across the company; test, promote solutions and mentor others with new AI technologies.



