✨ Dataspark is now Alomana - The future of AI Autonomy
Engineering · Remote (Europe)
At Alomana, we're building an ecosystem of intelligent agents designed to handle complex, real-world workflows across finance, enterprise operations, and beyond. Our architecture combines reasoning capabilities, advanced models and innovative orchestration engines to enable agents that are robust, transparent, and modular. We're looking for engineers who want to shape the future of AI autonomy.
We are looking for a highly skilled AI Engineer to help us design, build, and maintain intelligent systems that can reason, plan, and interact with structured and unstructured data. You will work at the core of our AI stack, contributing to the development of autonomous agents, semantic reasoning frameworks, and data-enhanced workflows.
This role requires a strong understanding of AI systems design, data pipelines, retrieval-augmented generation (RAG), and knowledge representation. You will collaborate closely with research engineers, product leads, and platform developers to implement scalable agent workflows that are interpretable and grounded in data.
• Design and implement AI agents capable of performing complex, multi-step tasks in real-world domains.
• Build and optimize data pipelines that integrate structured and unstructured sources for use in agent workflows.
• Implement and maintain retrieval-augmented generation (RAG) systems to enhance agent context and performance.
• Develop, maintain, and reason over knowledge graphs and memory systems used by agents.
• Contribute to the development of modular, scalable components in the agent architecture including planning, tool-use, and self-reflection layers.
• Collaborate with backend, product, and research teams to integrate AI capabilities into production-grade systems.
• Evaluate performance and robustness of agent behaviors and suggest improvements to architecture and design.
• Stay current with emerging trends in AI, including cognitive architectures, agentic workflows, and reasoning systems.
• 3+ years of experience in AI, machine learning, or related fields.
• Strong programming skills in Python and a deep understanding of AI system architectures.
• Experience designing and implementing intelligent agents or multi-component AI systems.
• Proficiency in retrieval-augmented generation (RAG), including integration with vector search and document stores.
• Experience working with or building semantic data structures such as knowledge graphs.
• Familiarity with modern data processing pipelines and API integrations.
• Demonstrated ability to build, evaluate, and improve autonomous decision-making systems.
• Strong problem-solving skills, with a balance between theoretical rigor and practical implementation.
• Excellent communication and collaboration skills.
• Experience in multi-agent systems or distributed AI architectures.
• Background in symbolic reasoning or hybrid AI techniques.
• Exposure to enterprise data systems, business workflows, or domain-specific AI applications.
• Contributions to open-source AI projects or published research in the field.
• Build state-of-the-art AI systems from the ground up.
• Work with a world-class team of engineers and researchers.
• Shape the future of AI in critical sectors like finance, enterprise ops, and decision automation.
• Flexible remote/hybrid work model.
• Competitive compensation, equity, and benefits.