Data & AI Architect – BD Excellence (BDE) Office

Job description

We are the people who give possibilities purpose BD is one of the largest global medical technology companies in the world. Advancing the world of health™ is our Purpose, and it’s no small feat. It takes the imagination and passion of all of us—from design and engineering to the manufacturing and marketing of our billions of MedTech products per year—to look at the impossible and find transformative solutions that turn dreams into possibilities. Job DescriptionSummary This position serves as a technical expert responsible for architecting and delivering AI-powered solutions that enable operational excellence, analytics, and decision-making across the BDE ecosystem. The role owns end-to-end solution design and implementation, including data integration, AI enablement, analytics delivery, and technology standards. Success is measured through scalable adoption, improved insight generation, reduced manual effort, and accelerated decision support. Success Profile Standardizes scalable AI architecture patterns, reusable components, and integration approaches. Delivers high-quality AI solutions that align with governance, security, and responsible AI standards. Enables measurable improvements in insight quality, speed to decision, and user adoption. Reduces manual data maintenance through automated connectors, pipelines, and synchronization processes. Builds alignment across technical and business stakeholders in a complex matrixed environment. Succeeds through collaboration, influence, and execution across global and cross-functional teams. Key Responsibilities: Design end-to-end AI architectures that integrate structured and unstructured enterprise data sources. Define scalable patterns for AI integration across collaboration, analytics, workflow, and internal platforms. Develop and deploy AI-enabled solutions using programming languages, APIs, cloud services, and modern frameworks, including large language model (LLM) and agentic AI architectures. Build and maintain automated data pipelines, connectors, and synchronization processes, leveraging modern data engineering platforms (e.g., Databricks, Snowflake). Prototype and move into production capabilities including document intelligence, analytics copilots, natural language querying, and insight generation. Partner with analytics and data teams to optimize data models and architectures for AI use cases. Apply AI and advanced analytics to identify insights, trends, and leading indicators supporting operational excellence. Enable embedded and conversational analytics experiences within existing business workflows and platforms. Define and promote technical standards, reusable components, and best practices across the BDE ecosystem. Mentor developers and analysts on AI solution development and integration approaches. Skills and Competencies: Execution Excellence: Delivers scalable solutions from concept through production deployment. Functional Expertise: Deep knowledge of AI architecture, software engineering, analytics, and data integration. Stakeholder Leadership: Builds strong partnerships across business and technical teams. Influence Without Authority: Drives adoption of standards and solutions across matrixed environments. Operational Rigor: Ensures alignment with governance, security, and responsible AI requirements. Data-Driven Decision Making: Applies analytics and insights to improve outcomes and performance. Strategic Communication: Translates complex technical concepts into actionable business recommendations. Change Leadership: Supports adoption of new capabilities and ways of working. Continuous Improvement Mindset: Identifies opportunities to optimize processes, solutions, and user experiences. Education, Qualifications, and Experience Education: Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field required. Master's degree in Computer Science, Artificial Intelligence/Machine Learning, Data Science, or a related quantitative/technical field strongly preferred. Experience: 10+ years of progressive experience in software engineering, data engineering, or AI/ML architecture, with a demonstrated track record of designing and deploying production-grade, end-to-end AI solutions. Hands-on experience architecting AI agents, copilots, chatbots, or retrieval-augmented generation (RAG) solutions using LLM APIs (e.g., Claude, Azure OpenAI, or equivalent). Practical experience with modern data engineering and analytics platforms (e.g., Databricks medallion/lakehouse architecture, Delta Lake, PySpark, Snowflake). Experience integrating multiple enterprise data sources and systems through APIs, connectors, and automated data pipelines. Proven ability to move from concept to production-ready solutions in complex, matrixed enterprise environments. Experience applying responsible AI, data governance, and security/compliance frameworks (e.g., SOC 2, GDPR, HIPAA, or equivalent) is a plus, particularly in regulated industries. Qualifications: Strong hands-on development experience with Python and SQL; working knowledge of cloud platforms (AWS, Azure, or GCP). Practical experience building and orchestrating GenAI/agentic solutions using frameworks such as LangGraph, Model Context Protocol (MCP), or comparable agent-orchestration and multi-agent tooling. Knowledge of analytics architectures, data modeling, and insight generation, including natural language querying and embedded/conversational analytics. Understanding of model lifecycle management, evaluation, monitoring, and continuous improvement in production environments. Experience deploying solutions within enterprise governance and security frameworks. Familiarity with enterprise collaboration and analytics platforms (e.g., SharePoint, Confluence, ServiceNow, Monday.com), embedded AI experiences, and usage analytics. Technical Skills: Languages & Data: Python, SQL Data Engineering & Platforms: Databricks (Delta Lake, Unity Catalog, PySpark), Snowflake, dbt, ETL/ELT pipeline design AI & GenAI: LLM APIs, Retrieval-Augmented Generation (RAG), agent orchestration frameworks (e.g., LangGraph, MCP), natural language interfaces, model evaluation and observability Cloud & Infrastructure: AWS, Azure, and/or GCP; Docker; Kubernetes; CI/CD (e.g., GitHub Actions) Integration: REST APIs, connectors, and workflow automation across enterprise systems (e.g., SharePoint, Confluence, ServiceNow, Monday.com) Analytics & Visualization: Power BI, Tableau, or equivalent embedded analytics tools Governance & Security: Responsible AI practices, data privacy/compliance frameworks (e.g., SOC 2, GDPR, HIPAA-equivalent) At BD, we prioritize on-site collaboration because we believe it fosters creativity, innovation, and effective problem-solving, which are essential in the fast-paced healthcare industry. For most roles, we require a minimum of 4 days of in-office presence per week to maintain our culture of excellence and ensure smooth operations, while also recognizing the importance of flexibility and work-life balance. Remote or field-based positions will have different workplace arrangements which will be indicated in the job posting. For certain roles at BD, employment is contingent upon the Company’s receipt of sufficient proof that you are fully vaccinated against COVID-19. In some locations, testing for COVID-19 may be available and/or required. Consistent with BD’s Workplace Accommodations Policy, requests for accommodation will be considered pursuant to applicable law. At BD, we are committed to supporting our associates’ well-being, development, and success through a performance-based culture. For this position, BD offers a competitive compensation package along with the following benefits specific to this role: Annual Bonus Health and Well-being Benefits Medical coverage Health Savings Accounts Flexible Spending Accounts Dental coverage Vision coverage Hospital Care Insurance Critical Ill