Data & AI Architect – BD Excellence (BDE) Office

Information Technology Senior Management Forum; Franklin Lakes (NJ); On-site; USD 150,000 - 230,000; Full time

Job summary

BD is seeking a senior AI Architect to design and deliver AI-powered solutions across the enterprise, enabling operational excellence and decision support. The role focuses on end-to-end architecture, data integration, and scalable patterns, with emphasis on governance and responsible AI.

You will lead collaboration with analytics, data engineering, and business teams, driving production-grade AI initiatives, and mentoring engineers in a complex matrixed environment.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or related field.

Responsibilities

• Design end-to-end AI architectures that integrate structured and unstructured enterprise data sources.

Skills

Execution Excellence

Functional Expertise

Stakeholder Leadership

Influence Without Authority

Operational Rigor

Data-Driven Decision Making

Strategic Communication

Change Leadership

Continuous Improvement Mindset

Education

Bachelor's degree in Computer Science or related field

Master's degree in Computer Science/AI/ML or related field (strongly preferred)

Tools

Databricks

Snowflake

Delta Lake

PySpark

LLM APIs (Claude, Azure OpenAI)

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 Description

Summary

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