Product Delivery Lead - Commercial Data Science and AI

We're looking for an experienced, highly technical, and strategically minded Director - Product Delivery to guide our cross-functional teams in building and deploying next generation products using, machine learning, and Generative AI capabilities. You'll be the crucial link between technical execution and business strategy, ensuring our teams deliver high-quality, reusable, and scalable solutions that drive significant business value for our commercial and medical functions, while strictly adhering to all compliance and security standards.

This role requires a unique blend of deep technical expertise, architectural vision, strong leadership, and excellent communication skills to navigate complex technical decisions and manage a diverse set of stakeholder expectations.

Key Responsibilities

Technical Leadership & Product Architecture

• Product Architect & Vision: Act as a Product Architect, defining the technical vision and high-level design for our BBU project workstreams for AI/ML, and GenAI products. Ensure solutions are scalable, secure, and maintainable.
• Advanced AI/ML Architecture: Drive the technical implementation GenAI capabilities using  MCP servers, A2A architecture using agentic architecture to deliver accurate, contextually relevant, and customized solutions for various BBU user personas.
• Data Strategy: Leverage expertise in modern data platforms like AWS, Databricks, or Snowflake and using architectural patterns like Knowledge Graphs to manage internal BBU datasets.
• Technical Direction: Provide hands-on technical leadership and guidance across multiple teams, including Data Science, Data Engineering, API Development/Microservices, UX, and ML/GenAI Ops.
• Promote Reusability: Champion and enforce best practices for code quality, component reusability, and modular design to accelerate development and reduce technical debt.

Compliance, Security, & Delivery Management.

• Risk & Compliance Oversight: Proactively engage with Compliance and Security Teams throughout the product lifecycle to ensure all solutions adhere to stringent regulatory requirements (e.g., HIPAA, GxP, privacy laws) and internal security policies.
• Cross-Functional Delivery: Lead the technical delivery of complex products from concept through launch, ensuring on-time and high-quality results.

Stakeholder Alignment & Communication

• BBU Business Partnership: Work closely with Product Owners to translate the product roadmap and business requirements (related to BioPharmacy data or commercial needs) into clear, actionable technical specifications.
• Cross-Team Collaboration: Engage actively with stakeholders from critical teams, including the Sales Force Team and the Insights & Analytics Team, to gather requirements, integrate our products with their platforms, and ensure the delivered solutions meet their high standards for quality and utility.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
• 7+ years of progressive experience in software engineering, data architecture, or related technical roles, with at least 3 years in a leadership or delivery-focused role.
• Deep familiarity with the BioPharmacy Business domain or other complex life sciences/pharmaceutical domains.
• Proven experience handling and guiding teams on Knowledge Graph implementation and maintenance.
• Demonstrated experience architecting and implementing Retrieval Augmented Generation (RAG) systems.
• Understanding of Medical, Legal, and Regulatory (MLR) review process, especially for GenAI outputs, accelerating time-to-market while maintaining compliance.
• Expert-level working knowledge of the AWS cloud platform and its core data/compute services.
• Highly Recommended: Deep working knowledge of Databricks or SnowFlake’s and its associated data processing frameworks.
• Proven experience working with Compliance and Security Teams to deliver regulated products (e.g., HIPAA, GxP).
• Expertise in Microservices architecture and building scalable REST APIs.

Preferred Qualifications

• Familiarity with specific AWS Generative AI architecture patterns, including Amazon Bedrock and implementing Agentic Core/RAG solutions.
• Prior experience with Snowflake or similar modern cloud data warehouses.
• Direct experience integrating products with CRM platforms like Salesforce.
• Prior experience leading teams building production-grade Data Science or Machine Learning products in the pharmaceutical or biotech industry
  

Office Working Requirements

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That’s why we work, on average, a minimum ofthree days per weekfrom the office. But that doesn’t mean we’re not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

Equal Opportunities

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.

Date Posted

Closing Date

Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.