Role Description En NEORIS estamos buscando un/a AI Agents Engineer SR para participar en proyectos de transformación digital y automatización inteligente, diseñando e implementando agentes de Inteligencia Artificial orientados a optimizar procesos a lo largo de todo el ciclo de vida del desarrollo de software (SDLC). El rol es 100% remoto para Argentina, con fuerte foco en orquestación de agentes, LLMs, prompt engineering avanzado e integración segura de IA en entornos productivos. Responsabilidades - Diseñar, desarrollar e implementar agentes de IA específicos por proyecto, alineados a objetivos de negocio y técnicos. - Orquestar múltiples agentes de IA y herramientas inteligentes, asegurando su correcta interacción e integración con plataformas existentes. - Aplicar prompt engineering avanzado para mejorar la precisión, consistencia y calidad de los resultados generados por modelos de IA. - Impulsar el desarrollo asistido por IA en actividades como análisis y resolución de bugs, generación de historias de usuario, testing y QA. - Crear, mantener y optimizar documentación técnica y funcional asistida por agentes de IA. - Implementar integraciones de IA contemplando seguridad, privacidad, compliance y gobierno del uso de modelos. - Automatizar procesos y flujos de trabajo mediante IA, incrementando la productividad de los equipos de desarrollo y gestión. - Colaborar de forma transversal con equipos de desarrollo, infraestructura, seguridad y management para asegurar una adopción efectiva de soluciones basadas en IA. Qualifications - Experiencia sólida en diseño y arquitectura de agentes de IA. - Conocimientos en orquestación de agentes y workflows inteligentes. - Experiencia comprobable en prompt engineering avanzado. - Trayectoria en AI-assisted development aplicado al SDLC. - Conocimiento profundo de las distintas etapas del ciclo de vida del desarrollo de software. - Experiencia en automatización de procesos y flujos de trabajo. - Conocimientos en integraciones seguras de IA, gobernanza y compliance. - Capacidad para trabajar de forma transversal con equipos técnicos y de negocio. - Nivel de inglés intermedio/avanzado. Benefits - Cobertura médica premium: Plan de salud de primera línea completamente cubierto para vos y tu familia. - Soporte para home office: Bono de conectividad para tus necesidades de trabajo remoto. - Capacitaciones: Descuentos en clases de inglés y acceso a Udemy. - Tiempo de deporte: Beneficios y descuentos en gimnasios. - Tiempo para vos: Vacaciones flexibles y día libre en tu cumpleaños. - Desarrollo profesional continuo: Oportunidades de aprendizaje y crecimiento constante.

Role Description We’re looking for a highly skilled AI Engineer to help us design, build, and scale intelligent systems across our next-generation global HR Tech platform. As an early-stage startup, we’re looking for someone who thrives in dynamic environments, is passionate about automation and AI-driven innovation, and brings hands-on experience developing AI/ML solutions within enterprise-grade SaaS platforms. This role reports directly to the Head of Engineering. - Design and implement machine learning models to solve HR-specific challenges (e.g., intelligent automation, anomaly detection, personalized experiences) - Collaborate with product managers and engineers to bring AI features to life across the platform - Develop and optimize data pipelines to support model training and inference - Research and apply NLP, LLMs, and other AI/ML technologies to streamline and improve HR workflows - Monitor model performance and retrain/improve based on feedback and usage - Build scalable AI solutions using cloud-native tools (preferably AWS) - Contribute to data governance, ethical AI use, and compliance Qualifications - 4–6+ years of experience as an AI/ML Engineer or Data Scientist, ideally with startup or SaaS exposure - Strong understanding of supervised/unsupervised learning, NLP, neural networks, and generative AI - Proficiency with Python and ML frameworks like TensorFlow, PyTorch, Hugging Face, or similar - Experience deploying models in production using cloud platforms like AWS Sagemaker, GCP Vertex AI, or Azure ML - Experience with data versioning, MLOps, and model lifecycle management - Ability to work autonomously and thrive in a startup environment - Familiarity with HR tech, payroll, or workforce data is a plus

Role Description Kumo is building the next generation of AI for structured data. With our Relational Foundation Model (RFM), we help some of the world’s largest companies transform their data into predictions, decisions, and end-to-end automated systems. Our culture is collaborative, fast-moving, and deeply user-obsessed. We value people who take initiative, learn quickly, communicate clearly, and enjoy solving hard technical + people challenges. Demand for Predictive AI is accelerating faster than ever. Our customers include some of the world’s most influential enterprises across retail, e-commerce, consumer goods, fintech, travel, and technology. - Operate at true global scale - Hundreds of ML models - Billions of data points - Business-critical use cases across recommendations, forecasting, supply chain optimization, fraud, CRM, and more We are rapidly expanding our Applied Machine Learning team, a high-impact, highly technical group that sits at the center of our customer engagements. This team guides customers from their very first pilot all the way through to scaled, production-grade deployments of relational predictive models. This is a unique opportunity for someone who is: - Curious and intellectually hungry - Energized by startup culture - Motivated by high-growth environments - Excited to become an expert practitioner of cutting-edge AI models - Thrilled by the chance to work directly with Silicon Valley innovators, global brands, and leaders in data science and business What You’ll Do - Support and eventually own technical success for enterprise customers adopting the Kumo platform. - Design and build prototypes, workflows, and models across use cases such as: - Recommendations & personalization - Forecasting & demand planning - Fraud detection & risk modeling - Supply chain & logistics optimization - Banking & financial analytics - CRM/growth marketing & user modeling - Work hands-on with large-scale relational datasets, customer pipelines, and production ML systems. - Guide customers through modeling choices, data structures, evals, trust, interpretability, and rollout plans. - Translate ambiguous customer needs into concrete ML solutions and RFM workflows. - Collaborate closely with Kumo engineering and research teams to improve platform capabilities. - Act as a technical leader and trusted advisor, understanding that deploying ML is as much a people and business challenge as it is a technical one. - Deliver demos, workshops, best practices, and partner with executives, PMs, analysts, and data scientists. Qualifications - Bachelor’s or Master’s in a STEM field (CS, EE, Math, Physics, Stats, etc.). - Strong fundamentals in data science, statistics, or machine learning coursework. - Real-world experience via internships, research, industry work, or substantial project work. - Demonstrated intellectual curiosity and initiative, personal ML/AI projects, open source, research, hackathons, or other hands-on experience. - Strong communication skills; comfortable working with people and navigating technical + non-technical audiences. - Genuine enthusiasm for ML/AI, modern modeling approaches, and applying them to real business problems. - Motivated, self-driven, excited to learn fast, and comfortable in a high-velocity startup environment. Requirements - Deeper expertise in one or more of: - ML infrastructure / data engineering - Full-stack development for ML apps - LLM orchestration, agent systems, or model tuning - Large-scale distributed systems - Forecasting, recsys, fraud, or other applied ML domains - Familiarity with GNNs, temporal models, or structured reasoning. - Enterprise integrations, data platforms, or productionizing ML Success Looks Like (First 3–6 Months) - Support and eventually lead multiple major customer engagements, delivering real business impact. - Solve multiple challenging predictive machine learning problems, by applying data science skills to large-scale datasets. - Build prototypes and workflows using RFM that demonstrate value and drive adoption. - Collaborate with engineering to improve reliability, performance, and model quality across use cases. - Earn trust from customer technical teams and become their go-to person for ML strategy and execution. Benefits - Exposure to an extraordinary range of challenges and industries. - Learn faster due to diverse customer problems and datasets. - Support and eventually lead technical engagements with large, forward-thinking companies. - Build advanced predictive systems using GNNs, temporal models, forecasting engines, and next-generation workflows. - Work cross-functionally with engineering, ML research, product, and executive leaders. - Help define what enterprise ML looks like in practice.

• As a Senior AI Engineer focused on Agentic Evaluation and Verification and Validation (V&V), you will join the AI and Data Science team within Slingshot’s Research and Development organization. • You will contribute to advancing how intelligent systems are evaluated and validated for mission-critical space operations. • This role focuses on building and scaling evaluation frameworks, benchmarks, and simulation-backed validation systems for agentic AI systems, including multi-step, tool-using, and autonomous decision-making workflows powered by LLMs and reinforcement learning. • Your work will directly support the development of reliable and trustworthy autonomous mission planning systems. • You will partner closely with AI researchers and domain experts to translate real-world mission concepts into structured, testable evaluation systems.