Inteligencia Artificial jobs in United States

Principal Enterprise Architect Data & AI Commercial- GEA IT

Introduction to role

Our Commercial Enterprise Architecture team supports the global development of platforms and solutions to enhance AstraZeneca's Global Business across Commercial, Medical, Market Access, and Patient Business capabilities. The Principal Enterprise Architect for Commercial Data and AI will drive the strategy and architecture for Data and AI Platforms within the Commercial Domain. This role involves working with pioneering technologies such as Amazon Q, Sagemaker, Amazon Bedrock, OpenAI, DataBricks, Redshift, Snowflake, and more. Collaborate with engineering teams and other business units to provide vital designs, patterns, reference architecture, frameworks, and services focused on data ingestion, extraction, processing, transformation, transport, storage, visualization, security, and knowledge representation. Your work will support the fundamental elements of the data world for AstraZeneca's global Commercial businesses.

Accountabilities

- Collaborate with Commercial IT and Business professionals to augment digital transformation efforts by identifying and piloting use cases. Discuss feasibility and architectural design with business teams and translate business leaders' vision into realistic technical implementation.
- Align technical implementation with existing and future requirements by capturing inputs from multiple collaborators — business users, Commercial IT Data scientists, security professionals, data engineers and analysts, and IT operations — and developing processes and products based on these inputs.
- Play a key role in defining the Commercial Data and AI architecture and selecting appropriate technologies from a pool of open-source and commercial offerings. Ensure new tools are well-integrated with existing data management and analytics tools.
- Work closely with security and risk leaders to foresee and mitigate risks such as training data poisoning, AI model theft, and adversarial samples. Ensure ethical AI implementation and restore trust in AI systems while staying updated with upcoming regulations.
- Plan data and AI architecture and pipelines. Understand the workflow and pipeline architectures of ML and deep learning workloads. Possess in-depth knowledge of components and architectural trade-offs involved across data management, governance, model building, deployment, and production workflows of AI.
- Apply software engineering and DevOps principles, including knowledge of DevOps workflows and tools such as Git, containers, Kubernetes, and CI/CD.
- Use data science and sophisticated analytics tools (such as SAS, R, Python) along with applied mathematics, ML frameworks (such as TensorFlow), and ML techniques (such as random forest and neural networks).
- Provide thought leadership to help the organization adopt a Data and AI-driven approach. Take a pragmatic approach to the limitations and risks of Data and AI while projecting a realistic picture to IT executives.
- Foster a collaborative attitude to ensure that the Commercial Data and AI platforms deliver both business and technical requirements. Collaborate optimally with data scientists, data engineers, data analysts, ML engineers, other architects, business unit leaders, and CxOs.

Essential Skills/Experience

- Bachelor’s Degree or equivalent experience in Data Science or AI engineering or related field.
- Experience in leading and delivering enterprise Data and AI platform architectural thinking and its practical application.
- Experience in conceptual and logical data modeling technologies.
- Experience in defining and working with information and data regulatory governances.
- Blend of data/information architecture, analysis, and engineering skills.
- Experience in known industry IT architectural patterns and methodologies (e.g., Redshift Amazon Bedrock, Amazon Q, Sagemaker).
- Understanding of AI Platforms concepts and cloud-based containerization strategies for hybrid cloud environments.
- Familiarity with AI lifecycles based on business use cases.

Desirable Skills/Experience

- Post-graduate degree in MIS or AI.
- Extensive experience in a senior AI/Data Science/Data Engineering role with practical examples of designing end-to-end data architecture designs or blueprints for substantial real-world use cases.
- Experience with AI and Data Governance frameworks in a commercial organization.
- Experience in Agile AI definition scrums.
- Proficiency in tooling such as metadata cataloging tools, data modeling tools, EA tools.
- Hands-on experience in AI model building (LLM/LVM) working closely with different data types to generate clear accuracy models.
- Experience working in the AI Pharmaceutical industry.

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 of three days per week from 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.

At AstraZeneca, we connect the dots across the business to improve agility and functionality of our processes to accelerate our journey to the next level. Our team of highly qualified professionals are persuasive communicators who negotiate with empathy. We are always mindful of the human impact of the changes we drive which helps us reach better complete solutions for the business.

Ready to make an impact?

Apply now!

Date Posted

Closing Date

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.