• Assist in the development and testing of agentic AI systems, including Multi-Agent and Agent-to-Agent (A2A) workflows, leveraging common industry standards such as the Model Context Protocol (MCP) to create interoperable AI agents. • Support the implementation of MCP Tools and Resources that enable Large Language Models (LLMs) to interact with internal systems and APIs in a secure, standardized manner. • Collaborate with engineers and data scientists to contribute to the architecture of a centralized "AI Gateway" that provides a unified, platform-independent interface for leveraging various LLMs. • Help implement observability pipelines to track trace-level data, monitor model latency, and support the optimization of Generative AI systems in production. • Work closely with senior team members to translate strategic designs into functional, production-ready solution components. • Participate in the implementation of AI guardrails to filter inputs and outputs, supporting data security, integrity, and the prevention of adversarial attacks such as prompt injection. • Assist in the design and implementation of Retrieval-Augmented Generation (RAG) pipelines to enhance LLM accuracy and grounding with enterprise data sources. • Learn and apply engineering best practices including version control (Git), automated testing, and CI/CD processes for AI systems. • Stay current with emerging trends in agentic AI, operational AI, and MLOps, and contribute ideas to continuously evolve the team's capabilities.

Do you want to join a team where the mission is meaningful, the challenges are complex, and you can directly see the results of your hard work? Lundbeck is a global biopharmaceutical company focusing exclusively on brain health. With more than 70 years of experience in neuroscience, we are committed to improving the lives of people with neurological and psychiatric diseases. Lundbeck employees are inspired and driven by our purpose to advance brain health and transform lives. Join us on our journey of growth! Remote opportunity - Open to candidates anywhere in the greater United States SUMMARY: We are seeking a highly skilled and forward-thinking AI Engineer to design, develop, and scale generative AI solutions across the organization. This role will play a critical part in translating emerging AI capabilities into enterprise-grade applications that drive business value, operational efficiency, and innovation. You will work cross-functionally with data scientists, IT, compliance, and business stakeholders to deliver secure, scalable, and production-ready AI solutions. ESSENTIAL FUNCTIONS: - Design, build, and deploy scalable GenAI applications leveraging LLMs, RAG architectures, and foundation models. - Develop and optimize advanced retrieval and context engineering strategies using internal knowledge bases and structured/unstructured data. - Design and orchestrate multi-step AI agents capable of reasoning, retrieval, and action execution across business workflows. - Contribute to enterprise GenAI architecture, ensuring modularity, reusability, scalability, and observability. - Build reusable GenAI components and services (agent frameworks, chat interfaces, orchestration layers, evaluation pipelines). - Integrate AI systems with enterprise platforms (CRM, document management, APIs) using secure authentication and governance standards. - Embed Responsible AI principles including privacy, compliance, auditability, explainability, and risk management. - Continuously evaluate emerging models and tools, benchmark performance, and optimize cost, latency, and system efficiency. REQUIRED EDUCATION, EXPERIENCE, and SKILLS: - Accredited Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. - 3+ years of relevant experience in software engineering, or AI development. - Proven experience developing Generative AI applications, including content generation, conversational AI, and natural language understanding tasks. - Strong proficiency in programming languages such as Python, Java or C++. - Experience with: - REST APIs, - LLM APIs (OpenAI, Azure OpenAI, Anthropic, etc.), - RAG architectures (vector databases such as Pinecone, FAISS, Weaviate, etc.), - LangChain, LlamaIndex, or similar orchestration frameworks, - Cloud platforms (Azure, AWS, or GCP). - Solid understanding of software engineering best practices (CI/CD, version control, testing, documentation). - Knowledge of AI risk, security, and data privacy principles. - Familiarity with AI deployment techniques, including Docker and Kubernetes for scalable production environments. - Strong problem-solving ability to design, develop, and optimize AI applications to meet specific business needs. - Ability to collaborate with cross-functional teams to drive successful deployment and integration of AI solutions. PREFERRED EDUCATION, EXPERIENCE, and SKILLS: - Accredited Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. - Experience deploying AI solutions in regulated production environments. - Experience with model fine-tuning or open-source LLM deployment. - Familiarity with MLOps/LLMOps frameworks. - Understanding of AI governance frameworks and responsible AI principles. - Experience with agent-based systems and multi-step workflows. - Exposure to UI/UX implementation and integration for AI-powered applications. - In-depth experience working with pharmaceutical datasets (first-party patient data, third-party claims, EHR, demand data). - Familiarity with regulatory standards in the pharmaceutical industry (e.g., GxP, ALCOA+). - Strong Preference to be based in Deerfield, IL Office TRAVEL: - Willingness/Ability to travel up to 20% domestically. International travel may be required. - If based remotely, additional travel will be required to Deerfield, IL, to meet the needs of the role and the business The range displayed is a national range, and if selected for this role, may vary based on various factors such as the candidate’s geographical location, qualifications, skills, competencies, and proficiency for the role. Salary Pay Range: $150,000 - $175,000 and eligibility for a 15% bonus target based on company and individual performance, and eligibility to participate in the company’s long-term incentive plan. Benefits for this position include flexible paid time off (PTO), health benefits to include Medical, Dental and Vision, and company match 401k. Additional benefits information can be found on our career site. Applications accepted on an ongoing basis. Why Lundbeck Lundbeck offers a robust and comprehensive benefits package to help employees live well and protect their health, family, and everyday life. Information regarding our benefit offering can be found on the U.S. career site. Lundbeck is committed to working with and providing reasonable accommodations to disabled veterans and other individuals with disabilities during our employment application process. If, because of a disability, you need a reasonable accommodation for any part of the application process, please visit the U.S. career site. Lundbeck is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status, and any other characteristic protected by law, rule, or regulation. Lundbeck participates in E-Verify.

Role Description As a Software Engineer, Artificial Intelligence, you will play a key role in building, operating, and continuously improving AI-driven systems that support internal business capabilities. You will focus on designing and maintaining AI-powered data pipelines, agent-based solutions, and LLM-driven services, working closely with modern data and ML platforms. This role requires strong software engineering foundations combined with hands-on experience in large language models, vector stores, and ML lifecycle management. You will contribute to scalable, production-grade AI solutions while driving quality, reliability, and continuous improvement across the full model and data pipeline lifecycle. - Build and maintain AI-powered data pipelines and extraction processes (batch and streaming) from internal relational data sources and unstructured documents (PDF, Word, PowerPoint) into structured datasets within Databricks. - Own end-to-end delivery of AI solutions, from design through production. - Design and manage text embeddings and vector stores within Databricks for use with vector indexing and retrieval solutions. - Drive architecture and best practices for AI-powered systems. - Design, develop, and maintain custom tools implemented as MCP servers and Databricks applications to extend agent and model capabilities. - Design, develop and implement AI Agents using frameworks like LangChain and LangGraph. - Implement LLM scorers to validate and monitor agents, applications and models. Prevent issues like hallucinations or unnecessary actions through structured testing and guardrails. - Drive continuous improvement through prompt engineering, pipeline optimization, vector store tuning, and scorer refinement to ensure high-quality LLM responses. - Collaborate on production deployments, monitoring, and scalability of ML and LLM-based services. Qualifications - 5-8 years of industry experience in software engineering or related roles. - Strong proficiency in Python, including production services, asynchronous programming, and testing. - Hands-on experience with AI Agents Development frameworks such as LangChain, LangGraph and LlamaIndex. - Experience using MLflow for prompt engineering, experimentation, evaluation, model registry, and deployments. - Solid understanding of vector databases (e.g., FAISS, Pinecone, Weaviate, Chroma or similar), including serverless or managed options. - Experience implementing Retrieval augmented generation (RAG) solutions. Data Ingestion and Retrieval, LLM Generation. - Experience building and consuming REST APIs, model serving solutions, and CI/CD pipelines. - Experience working with cloud platforms (AWS), containerization (Docker), and modern deployment practices. - Hands-on experience with Databricks, Apache Spark, and Delta Lake (nice to have). - Advanced English level, both written and verbal.

• Design and develop AI agents using frameworks such as LangGraph and MCP-based architectures • Build agent interaction layers using tools such as CopilotKit, Vercel AI SDK, or similar • Develop and deploy AI services in AWS or Azure environments • Design and implement SAP integrations using OData services, Function Modules, CDS views, and APIs • Work with SAP data models to enable contextual retrieval and automation workflows • Collaborate with SAP Basis teams on connectivity, performance, and access management • Integrate AI capabilities into incident management and ticketing workflows such as ServiceNow • Develop reusable AI components supporting SAP-focused automation and operations • Collaborate with product and managed services teams to deliver production-ready AI systems