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Summary We are seeking a Senior Software Engineer (Applied AI) who can help us build the next generation of AI-powered workflows at Avallone. This is a hands-on engineering role focused on turning recent advances in AI into reliable, valuable product capabilities for our customers. You'll work across product, engineering, and AI to identify opportunities, design solutions, and bring them into production. We’re looking for someone who combines strong software engineering fundamentals with practical experience building and operating AI-powered products in the real world. Location: Copenhagen (hybrid) Reporting line: CTO About the role You will help design, build, and operate AI-powered product capabilities in a security- and reliability-conscious production environment. This role is about shipping real customer value: robust workflows, measurable quality improvements, and systems we can understand, debug, and evolve over time. What you'll work on The following are some of the important areas you'll focus on: Designing and building AI-powered product capabilities that solve real customer problems. Improving retrieval, grounding, and answer quality across our AI systems. Building evaluation frameworks and feedback loops to measure and improve AI performance. Developing shared AI infrastructure, abstractions, and tooling that enable the wider engineering team. Exploring new AI capabilities and helping determine where they can create meaningful value for customers. Balancing quality, latency, reliability, security, and cost in production AI systems. Working closely with product and domain experts to turn complex KYC and compliance workflows into effective AI-assisted experiences. What we’re looking for Technical background Significant experience (typically 5+ years) as a software engineer building production systems. Strong proficiency with: TypeScript/Node.js or another modern backend language. Relational databases and distributed systems. Modern cloud environments (ideally AWS). Experience designing and operating customer-facing SaaS products. AI experience Demonstrated experience building and shipping AI-powered features or products used by real customers. Deep, hands-on expertise working with modern LLMs and AI platforms in production (not just prototypes), including making the right tradeoffs across quality, latency, reliability, and cost. Strong working knowledge and practical implementation experience across areas such as: Retrieval-Augmented Generation (RAG) Evaluation and benchmarking Prompt engineering and structured outputs Agents and tool use Embeddings and semantic search AI observability and monitoring Ability to reason rigorously about AI system behavior and failure modes (hallucinations, grounding gaps, prompt/agent brittleness, retrieval drift), and to design mitigations that are measurable and maintainable. Ways of working You are curious and actively experiment with new technologies. You can separate hype from practical value. You move quickly from idea to working prototype while maintaining engineering quality. You communicate clearly with both engineers and non-engineers. You enjoy working in areas where the solution is not yet obvious. Nice to have Experience building AI products in a regulated or compliance-heavy domain. Experience with evaluation frameworks and AI quality measurement. Experience with vector databases, search systems, or knowledge retrieval. Experience fine-tuning models or training domain-specific AI systems. Familiarity with KYC, AML, risk, compliance, or fintech workflows. Experience working in a startup environment with high autonomy and ownership. Engineering at Avallone Engineering at Avallone means being part of a small, non-hierarchical agile team where everyone’s voice matters. We work closely together, keeping collaboration at the ce