Senior AI Engineer

<p>At Genmab, we are dedicated to building extra[not]ordinary® futures, together, by developing antibody products and groundbreaking, knock-your-socks-off KYSO antibody medicines® that change lives and the future of cancer treatment and serious diseases. We strive to create, champion and maintain a global workplace where individuals’ unique contributions are valued and drive innovative solutions to meet the needs of our patients, care partners, families and employees.</p><p></p><p>Our people are compassionate, candid, and purposeful, and our business is innovative and rooted in science. We believe that being proudly authentic and determined to be our best is essential to fulfilling our purpose. Yes, our work is incredibly serious and impactful, but we have big ambitions, bring a ton of care to pursuing them, and have a lot of fun while doing so.</p><p></p><p>Does this inspire you and feel like a fit? Then we would love to have you join us!</p><p><b><span>Senior AI Engineer </span></b></p><p><span> </span></p><p><span><span>As a Senior AI Engineer in Genmab’s AI Lab, you’ll sit at the intersection of software engineering and applied AI. This role is about building robust, production-ready tools</span><span>, </span><span>using large language models (LLMs), agent-based frameworks, and modern cloud infrastructure</span><span> </span><span>to support drug discovery, clinical trials, and data-driven decision-making.</span></span><span> </span></p><p></p><p><span><span>You’ll join a small, hands-on team working directly with domain experts across the company. Your focus will be to turn high-potential AI prototypes into scalable, useful tools that make an impact across the business</span><span> </span><span>from the lab to the field.</span></span><span> </span></p><p><span><span>This is an engineering-focused role, not a traditional data science position. You’ll need to be comfortable designing systems, writing code, deploying to production, and supporting ongoing use</span><span> </span><span>all while staying aligned with Genmab’s mission to improve patients’ lives.</span></span><span> </span></p><p></p><p><b><span>Responsibilities</span></b><span> </span></p><ul><li><span><span>Architect and build multi-agent systems using frameworks like A2A or MCP to enable autonomous and human-in-the-loop workflows (e.g. document drafting, data analysis).</span></span><span> </span></li><li><span><span>Develop backend services with Python and FastAPI</span><span>, and create light frontends with </span><span>Streamlit</span><span> or React when needed.</span></span><span> </span></li><li><span><span>Integrate systems with graph and vector databases (e.g. Neo4j, Pinecone) and Genmab’s data infrastructure on AWS.</span></span><span> </span></li><li><span><span>Embed AI tools (e.g. GitHub Copilot, Replit</span><span>) into internal developer workflows to increase efficiency and adoption.</span></span><span> </span></li><li><span><span>Own the path from prototype to production, ensuring tools are reliable, secure, and scalable—avoiding throwaway solutions.</span></span><span> </span><span><span>Collaborate across teams, understanding business needs and translating them into technical solutions with real-world value.</span></span><span> </span></li><li><span><span>Explore and apply emerging AI technologies, sharing insights internally and supporting a culture of learning and experimentation.</span></span><span> </span></li></ul><p></p><p><b><span>Requirements</span></b><span> </span></p><ul><li><span><span>8+ years of experience in software or ML engineering, including 1+ year working with applied LLMs (e.g. RAG, agents, context engineering).</span></span><span> </span></li><li><span><span>Strong software engineering skills with Python (FastAPI</span><span>, backend development) and some experience with <span>JavaScript/TypeScript</span> (React/Next.js) preferred.</span></span><span> </span></li><li><span><span>Familiarity with one or more agent frameworks (e.g. LangGraph</span><span>, </span><span>LangChain</span><span>, </span><span>AutoGen</span><span>, </span><span>AgentSDK</span><span>) and orchestration libraries.</span></span></li><li><span><span>Understanding of ML fundamentals: transformers, embeddings, vector search, and evaluation methodologies.</span></span><span> </span></li><li><span><span>Experience working with cloud infrastructure and dev ops tools for production deployment (preferably AWS).</span></span><span> </span></li><li><span><span>Strong communication skills<span> </span>able to collaborate with scientists, engineers, and business teams.</span></span><span> </span></li><li><span><span>A self-starter with a strong sense of ownership, eager to explore new technologies and solve meaningful problems.</span></span><span> </span></li><li><span><span>Interest in life sciences or the biotech/pharma space is a big plus—but domain expertise is not required on day one.</span></span><span> </span></li></ul><p><span>