Articul8 is an enterprise domain-specific generative AI platform that provides multimodal industrial data intelligence and multi-agent reasoning for mission-critical and regulated industries.
About Us: Articul8 was born from a simple belief: GenAI should work for the enterprise, not the other way around. Our platform — combining domain-specific models, autonomous agentic reasoning (ModelMesh™), reliable model evaluation (LLM-IQ™), and multimodal understanding — serves regulated industries such energy, semiconductor, finance, aerospace, supply chain, and more. Trusted by Fortune 500 enterprises, we bring together research, engineering, product, and domain expertise to deliver AI that meets the accuracy, explainability, and auditability standards that high-stakes environments demand. Job Description: Articul8 AI is seeking an exceptional Product/Software Engineer-Backend to join us in shaping the future of Generative Artificial Intelligence (GenAI). We are looking for a Product/Software Engineer-Backend with a proven track record of designing and building scalable production-level software. As a member of our Product Technology team, you will play a critical role in designing, developing, and maintaining the backend software and infrastructure supporting our GenAI-powered products. You'll collaborate with cross-functional teams to drive innovation, optimize performance, and foster growth. This position offers exciting opportunities to work closely with cross-functional teams and external partners to drive innovations in enterprise-grade GenAI. Responsibilities: - Design, develop, test, deploy, maintain, and improve scalable, secure, and high-performance backend systems, focusing on high availability, low latency, and cost-effectiveness. - Be the subject matter expert in infrastructure when designing new products and introducing new technology to our existing product line. - Collaborate closely with engineering and research teams to integrate infrastructure components with product features, ensuring optimal system performance and user experience. - Design event-driven architectures and develop APIs and microservices to support real-time processing and analytics. - Ensure system reliability, performance, and scalability through monitoring, logging, and error handling mechanisms. - Stay up-to-date with emerging trends, technologies, and methodologies, applying this knowledge to enhance our infrastructure capabilities. - Participate in code reviews, contribute to open-source projects, and mentor junior engineers. Required Qualifications: - Professional experience: 7+ years of design, implementation, or consulting in applications and backend software development experience. - Education: BSc degree in Computer Science, Engineering, or a related field. Preferred Qualifications: - Technology stack: - Cloud Platforms: AWS, Azure, GCP - Programming/ Development: Python, Node.js, Go, Ruby, CI/CD pipelines, and version control. - Frameworks: Django, Flask, OpenAPI, FastAPI, Spring Boot, Express.js - Databases: PostgreSQL, MySQL, MongoDB, Redis - API Management: REST, GraphQL. - Container Orchestration: Kubernetes, Docker Swarm - Education: Master’s or PhD in Computer science or related technical fields. Professional Attributes (Code42): - Practice Humility: You ask questions even when you think you know the answer. You seek feedback early, learn from anyone regardless of title, and treat every experiment — especially the failures — as data. - Bias for Outcomes: You measure your work by what changed, not what you tried. You ship results, not slide decks. When a deadline is real, you find a way. - Care Deeply: You treat every problem as yours to solve. You review your own work with the rigor you'd want from a reviewer. You help teammates without being asked. - Dare to Do the Impossible & Embrace Scarcity: You set goals that make you uncomfortable. When told something can't be done, you find a way or a better question. Constraints sharpen your thinking, not slow it down. - Build a Better World: You believe AI should make things meaningfully better for real people. You hold yourself accountable not just for whether your model works, but for what it does in the world.