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Lead AI Engineer

June 26, 2026

Location: USA - RemoteAbout IXOPAYIXOPAY is the enterprise-grade global payment infrastructure platform built for the era of agentic commerce, equipping merchants and businesses with AI-driven intelligence, orchestration, advanced tokenization, and the tools to power every step of their payments journey. From routing and compliance to customized modules and full-scale orchestration, IXOPAY delivers the infrastructure for faster integrations, higher approval rates, and seamless global expansion.We believe our people are our most valuable asset and that our culture is defined by our core values that align the organization with our mission and strategy.About This RoleIXOPAY is built on three core products that power the full payments lifecycle for enterprise merchants worldwide. Our Payment Orchestration platform routes transactions intelligently across a global network of acquirers and payment methods through a single API. Our Tokenization platform (TokenEx) gives merchants true ownership of their payment data with universal, network, and agnostic tokens that eliminate PSP lock-in and dramatically reduce PCI scope. And our AI Payments Intelligence engine (Congrify) turns fragmented transaction data into actionable insights — optimizing authorization rates, identifying fee-saving opportunities, and powering predictive analytics across the stack.We're now making a deliberate bet: fully adopting AI not just in our software development lifecycle, but as a core part of our product portfolio. We see a future where intelligent agents accelerate how we deliver software, how our customers experience our platform, and how payments themselves are orchestrated. That means AI-powered code review and test generation in our SDLC. It means customer-facing agents that automate onboarding, troubleshoot integrations, and surface insights in natural language. And it means building agentic capabilities directly into our products — autonomous routing decisions, self-healing transaction flows, and real-time fraud arbitration powered by multi-agent systems.As our Lead AI Developer, you'll be at the center of all of it. This is a greenfield leadership role for someone who wants to own the AI stack, shape the roadmap, and build a team that delivers AI as both an internal accelerant and an external product.What You'll Do:<ul><li>Architect AI agent systems: Design, build, and deploy production single-agent and multi-agent systems using LangGraph on cloud AI platforms (Azure AI Foundry, AWS Bedrock, etc.), with Claude as the primary foundation model. Architect agent memory, state management, and context persistence for long-horizon reasoning tasks.</li><li>Own evaluation and quality: Build and maintain evaluation harnesses that measure faithfulness, hallucination rate, retrieval quality, latency, and instruction-following accuracy across model versions and prompt changes. Define golden test sets, regression suites, and automated eval pipelines that gate every release.</li><li>Build AI safety and guardrails: Implement safety guardrails, output filtering, and prompt injection defenses across all agent systems. Lead red-teaming exercises to identify failure modes before they reach production. Ensure responsible AI practices are embedded in every deployment.</li><li>Ship RAG-powered intelligence: Build agentic RAG pipelines with retrieval, generation, validation, and ReAct-style reasoning loops that ground outputs in real payment data. Leverage the Claude SDK, Anthropic's tool-use APIs, and MCP protocol to build agents that interact with internal systems, payment gateways, and external data sources.</li><li>Manage cost and performance: Own token cost modeling and inference optimization across agent workflows. Understand the cost profile of every agent loop at production scale and make architecture decisions that balance capability with spend.</li><li>Design human-in-the-loop patterns: Design human-in-the-loop review checkpoints and escalation paths for high-stakes workflows. Define where agents operate autonomously and where human oversight is required — especially in payment-critical operations.</li><li>Lead delivery streams: Own the AI delivery streams (Trust Score, StormTrooper, RFC Agent) from ideation through production deployment. Define technical direction, set quality standards, and make build-vs-buy decisions.</li><li>Instrument observability: Set up and maintain LLM observability and tracing infrastructure (LangSmith, LangFuse, or equivalent) to monitor agent behavior, debug failures, and track quality metrics in production.</li><li>Drive AI strategy: Partner with product, engineering, and payments teams to identify high-impact AI use cases — fraud scoring, intelligent routing, chargeback prediction, automated reconciliation, and beyond.</li><li>Build the team: Mentor contractors and future hires. Establish coding standards, review patterns, and engineering culture for the AI function.</li></ul>What You Bring:<ul><li>Extensive software development experience, with many years of your career focused on data science, machine learning, and/or agentic AI development (or a combination).</li><li>Demonstrated track record of building and deploying production-ready AI agents — not proofs of concept, not notebooks, but systems running in production with real users and real data. You can describe a specific production failure you caught, what the failure mode was, and what you built to prevent it.</li><li>Experience designing and running evaluation frameworks for LLM-powered systems — faithfulness scoring, hallucination detection, retrieval quality metrics, and regression testing across model and prompt changes.</li><li>Hands-on experience building agents with LangGraph (state machines, conditional edges, tool nodes, memory management, human-in-the-loop patterns).</li><li>Production experience with the Claude SDK / Anthropic API — tool use, MCP protocol, structured outputs, and prompt engineering at scale.</li><li>Understanding of AI safety practices: output filtering, guardrail implementation, prompt injection defense, and red-teaming methodologies.</li><li>Strong Python skills. You write clean, testable, well-documented code.</li><li>Experience with RAG architectures — vector stores (FAISS, Pinecone, OpenSearch), embedding models, chunking strategies, and retrieval evaluation.</li><li>Practical understanding of token cost modeling, inference optimization, and the trade-offs between fine-tuning, retrieval-based approaches, and prompt engineering at production scale.</li><li>Familiarity with cloud AI platforms (AWS Bedrock, Azure AI Foundry, GCP Vertex AI) and supporting cloud infrastructure services.</li><li>Experience with LLM observability and tracing tools (LangSmith, LangFuse, Arize, or equivalent) for monitoring agent behavior and quality metrics in production.</li><li>Ability to lead technical decisions and communicate trade-offs clearly to both engineering and business stakeholders.</li></ul>Nice to Have:<ul><li>Experience in payments, fintech, or financial services.</li><li>Background in NLP, information extraction, or document understanding.</li><li>Experience with fine-tuning approaches (LoRA, SFT, DPO/RLHF) and the judgment to know when fine-tuning is the right call versus retrieval or better prompting.</li><li>Prior experience scaling an AI/ML function from 0 to 1.</li><li>Contributions to open-source AI/agent frameworks.</li></ul>Our AI Stack:<ul><li>Foundation Models: Claude (Anthropic) via cloud AI platforms</li><li>Agent Framework: LangGraph / LangChain / MCP</li><li>Embeddings & RAG: Cloud embeddings, FAISS, OpenSearch</li><li>Infrastructure: AWS, Azure (Bedrock, AI Foundry, Lambda, ECS)</li><li>Languages: Python, TypeScript</li><li>Eval & Observability: LangSmith, LangFuse, Arize, Datadog</li><li>Safety & Guardrails: Custom guardrails, red-teaming, output filtering</li></ul>What We Offer<ul><li>Competitive salary and benefits</li><li>Opportunities for growth and development</li><li>A collaborative and supportive team environment</li></ul>US Benefits Include<ul><li>Medical, Dental & Vision Insurance</li><li>Flexible Spending Account (FSA) & Health Savings Account (HSA)</li><li>Employer-paid Life, AD&D, STD & LTD Insurance</li><li>Unlimited PTO & Paid Holidays</li><li>401(k) Plan with Employer Match</li></ul>Equal Opportunity EmployerIXOPAY is an Equal Opportunity Employer and provides equal employment opportunities to all employees and applicants without regard to race, color, religion, sex (including pregnancy, sexual orientation, and gender identity), national origin, age, disability, genetic information, veteran status, or any other status protected by applicable federal, state, or local law. IXOPAY participates in E-Verify.

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Common Interview Questions And Answers

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This is what this question poses: When do you focus and start working seriously? What are the hours you work optimally? Are you a night owl? A morning bird? Remote teams can be made up of people working on different shifts and around the world, so you won't necessarily be stuck in the 9-5 schedule if it's not for you...

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5. HOW DO YOU PROCESS INFORMATION?

Several years ago, I was working in a team to plan a big event. My supervisor made us all work as a team before the big day. One of our activities has been to find out how each of us processes information...

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Or you may receive even more specific questions, such as: What's on your calendar? Do you plan blocks of time to do certain types of work? Do you have an open calendar that everyone can see?...

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Just like your schedule, how you track files and other information is very important. After all, everything is digital!...

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The day I watched Marie Forleo's film separating the important from the urgent, my life changed. Not all remote jobs start fast, but most of them are...

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Just as communication is essential when working remotely, so is organization. Because you won't have those opportunities in the elevator or a casual conversation in the lunchroom, you should take advantage of the little time you have in a video or phone conference...

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This is a great question because it shows your comfort level with technology, which is very important for a remote worker because you will be working with technology over time...

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