Fractal Analytics

Join a fast-growing company as a Gen AI Engineer focused on AWS. The posting provides limited role-specific details but emphasizes a passionate, customer-focused workplace.

GenAI Engineer building production-grade generative AI and LLM solutions, from advanced RAG and agentic workflows to scalable APIs, pipelines, and reusable AI frameworks. The role combines model training and fine-tuning with architecture, evaluation, responsible AI, and direct stakeholder engagement.

Senior MLOps Engineer responsible for operationalizing machine learning solutions across model serving, data pipelines, feature engineering, and model lifecycle management. The role combines hands-on backend development with scalable ML platform engineering across development, test, and production environments.

Lead the architecture and delivery of scalable, secure Generative AI solutions for enterprise clients using LLMs, RAG, AI agents, and cloud platforms. The role combines hands-on AI/ML architecture with client engagement, pre-sales support, governance, and technical leadership.

Senior Test Engineer responsible for manual and automated testing, system configuration, and deployment support for a Card Management System in the financial services sector. The role combines functional, integration, and regression testing with stakeholder collaboration and quality improvement initiatives.

Lead the technical direction and hands-on development of Cogentiq I2C’s agentic AI capabilities, building dependable AI systems for invoice-to-cash workflows. You will manage the AI engineering team while personally tackling the hardest agent and model challenges.

Lead the engineering side of Cogentiq I2C, an agentic AI invoice-to-cash product, while designing its application, services, data platform, and infrastructure. This is a hands-on leadership role combining architecture, team leadership, product delivery, and substantial software development.

Build and operate production-grade machine learning systems and MLOps infrastructure for enterprise clients. This role focuses on automating model development, deployment, monitoring, and operations across cloud and on-premises environments.