• Design and build the core systems powering Jimdo Companion, including agent orchestration, recommendation engines, and scalable APIs. • Develop AI-powered features that automate real business tasks and improve customer outcomes. • Build high-quality backend services and engaging frontend experiences using modern full-stack technologies. • Design, evaluate, and optimise LLM-powered workflows, prompts, guardrails, and agent coordination. • Build reusable AI platform capabilities that empower other engineering teams to create AI-enabled products. • Partner closely with Product Managers, Designers, Data Analysts, and engineers to deliver customer-centric solutions. • Champion AI-augmented software development by leveraging modern AI coding assistants and sharing best practices across the engineering team.

• Design, develop and deliver AI-powered features end-to-end: from proof of concept to production on our Partner's stack (Angular, Node/TypeScript, PostgreSQL, Azure) • Evaluate and integrate AI/ML services, APIs, and open-source models to solve real customer problems (document processing, root-cause analysis, ERP/MES integrations) • Shape the AI/ML tech stack with real ownership over tools, frameworks, and architecture • Build and maintain eval frameworks to ensure AI outputs meet quality, reliability, and safety standards • Collaborate with product and engineering, identify high-impact AI opportunities, and grow AI competency across the team

Role Description We're looking for a Lead AI Developer to define and build the AI capabilities that will shape the future of IXOPAY. This is a greenfield leadership role with broad technical ownership. You'll lead the design and delivery of AI-powered products while embedding AI across our engineering organization—from intelligent developer tooling to customer-facing agents and autonomous payment workflows. Working closely with Product and Engineering, you'll establish our AI architecture, guide technical direction, and help build the team that delivers the next generation of AI-driven payment technology. What You'll Do - Design, build, and deploy production-ready AI agents and multi-agent systems. - Define the architecture for AI-powered products, including retrieval, memory, orchestration, and human-in-the-loop workflows. - Develop evaluation frameworks to measure quality, reliability, safety, latency, and overall model performance. - Implement AI guardrails, observability, and monitoring to ensure secure and responsible AI deployments. - Build intelligent workflows that automate onboarding, payment optimization, fraud detection, and operational decision-making. - Partner with Product and Engineering teams to identify high-impact AI opportunities across the platform. - Lead AI delivery from concept through production, balancing innovation, quality, scalability, and cost. - Mentor engineers, establish engineering standards, and help grow IXOPAY's AI capability. Qualifications - Extensive software engineering experience, with significant hands-on experience building production AI, machine learning, or agentic AI systems. - Proven experience deploying LLM-powered applications used by real customers at production scale. - Strong Python development skills with a focus on clean, maintainable, and well-tested code. - Experience designing evaluation frameworks for AI systems, including quality measurement, regression testing, and model validation. - Experience building AI agents using modern frameworks such as LangGraph, LangChain, or similar technologies. - Strong understanding of retrieval-augmented generation (RAG), vector search, prompt engineering, and agent orchestration. - Experience implementing AI safety practices, including guardrails, prompt injection protection, and human oversight. - Familiarity with cloud AI platforms such as AWS Bedrock, Azure AI Foundry, or Google Vertex AI. - Excellent communication skills and the ability to lead technical direction across cross-functional teams. Preferred - Experience in payments, FinTech, or other regulated industries. - Experience scaling AI platforms or engineering teams in a fast-growing environment. - Familiarity with LLM observability tools such as LangSmith, LangFuse, or Arize. - Experience with fine-tuning strategies and understanding when they provide value over retrieval-based approaches. - Contributions to open-source AI or machine learning projects. Our AI Stack - Foundation models including Claude via cloud AI platforms - LangGraph, LangChain, and the Model Context Protocol (MCP) - AWS Bedrock and Azure AI Foundry - Python and TypeScript - Vector databases and modern RAG architectures - LangSmith, LangFuse, Arize, and Datadog for evaluation and observability Benefits - Competitive salary and benefits - Professional growth and leadership opportunities - A collaborative, international engineering culture - The opportunity to build an AI function from the ground up US Benefits Include - Medical, Dental, and Vision Insurance - Flexible Spending Account (FSA) and Health Savings Account (HSA) - Employer-paid Life, AD&D, Short-Term Disability, and Long-Term Disability Insurance - Unlimited Paid Time Off and Paid Holidays - 401(k) Plan with Employer Match Our Commitment to Inclusion We know great candidates don't always meet every qualification. If you're excited about this opportunity, we encourage you to apply—we'd love to hear what you can bring to IXOPAY. Equal Opportunity Employer: IXOPAY is proud to be an Equal Opportunity Employer. We consider all qualified applicants without regard to race, color, religion, sex (including pregnancy, sexual orientation, gender identity, or gender expression), national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable law. IXOPAY participates in E-Verify.

Role Description We invite a skilled AI Engineer to join our team in building GPU-accelerated video analytics for real-time safety monitoring across large fleets and industrial environments. In this role, you’ll help design and optimize pipelines that detect and track actionable safety events in high-volume video streams. You’ll work on real-world systems that make an impact, collaborating with engineering and product teams to deliver reliable, high-performance solutions. Qualifications - 7+ years of software engineering experience with strong backend skills - 3+ years of experience shipping computer vision solutions to production - Strong Python proficiency - Experience with OpenCV, PyTorch, async I/O frameworks, and API integrations - Hands-on experience with YOLO/Ultralytics or similar object detection frameworks - Experience detecting, labeling, and tracking objects in video - Solid knowledge of frame sampling, confidence thresholds, temporal filtering, and multi-camera aggregation - Experience with GPU inference optimization (batching, stride, TensorRT, CUDA, quantization, throughput tuning) - Ability to communicate and collaborate effectively with engineering and product teams - Upper-Intermediate+ English level Requirements - Experience with Azure Event Hub, Blob Storage, Application Insights, or similar (desirable) - Familiarity with Docker, cloud deployments, and production monitoring systems (desirable) - Experience in temporal/sequence analysis for event detection (desirable) - Experience with video analytics in safety, compliance, or industrial/transportation environments (desirable) Key Responsibilities - Develop and maintain robust backend solutions that process video data and deliver actionable insights using pre-trained computer vision models. - Develop and optimize GPU-accelerated video inference pipelines for real-time processing. - Implement, evaluate, and improve object detection models (YOLO or similar). - Build temporal smoothing and tracking logic for safety event detection. - Optimize model performance using TensorRT, ONNX, CUDA, and GPU profiling tools. - Build and maintain integrations with event-driven APIs, Azure Event Hub, Blob Storage, and internal services. - Add metrics, logging, telemetry, and fail-safe mechanisms for resilient inference jobs. - Collaborate on dataset curation, labeling, model training, validation, and experiment tracking. - Support containerized deployments (Docker) and assist with monitoring and scaling production workload. Next Steps - Submit a CV in English - Intro call with a Recruiter - Internal interview - Client interview - Offer