Lead Consultant AI Application Engineering

Job Title: Lead Consultant - AI Application Engineering

Career Level:E

Introduction to role:

Are you ready to turn modern AI into reliable scalable applications that help accelerate the discovery and delivery of life-changing medicines Do you thrive at the intersection of hands-on engineering GenAI and product leadershiptranslating ideas into tools that scientists and business teams use every day

In this role you will lead full-stack delivery of AI-enabled products from architecture to production applying modern engineering practices to unlock data automate decisions and create seamless user experiences. You will guide multi-functional squads shape technical direction and ship secure high-quality solutions that scale across a global enterprise. With strong sponsorship and access to sophisticated platforms you will set the pace for how AI is designed built and adopted.

Accountabilities:

• Product Architecture and Strategy: Define technical direction for AI applications making pragmatic build-versus-buy choices and aligning roadmaps to measurable business outcomes.
• Full-Stack Delivery: Lead end-to-end engineering across front-end back-end APIs data layers and infrastructure to deliver resilient observable and secure applications.
• Machine Learning Pipelines: Operationalize models with robust data ingestion feature stores evaluation and monitoring to ensure accuracy reliability and drift management.
• Generative AI Integration: Apply LLMs and related techniques (prompting fine-tuning retrieval) to create new user experiences and automate knowledge-heavy workflows responsibly.
• Scalable Systems: Design for performance and elasticity optimizing cost and latency while ensuring compliance privacy and safe use of AI.
• Collaboration and Leadership: Partner with data scientists product managers and domain experts to frame problems test hypotheses and iterate quickly from prototype to production.
• Engineering Excellence: Uphold code quality patterns and standards; establish CI/CD testing strategies and documentation that make solutions maintainable and auditable.
• Innovation and Tech Evaluation: Maintain a clear tech radar; pilot emerging tools and methodologies and scale what works to raise engineering throughput and product impact.
• Operability and Reliability: Ensure robust SLOs on-call readiness telemetry and incident playbooks so applications remain dependable at enterprise scale.
• Capability Building: Mentor engineers grow skills in AI application engineering and develop a culture of curiosity perseverance and high performance.

Essential Skills/Experience:

• Bachelors or Masters degree in Computer Science Engineering or related field.
• Proven experience as a Full Stack Developer with a focus on AI and machine learning applications.
• Strong proficiency in programming languages such as Python JavaScript or .
• Experience with frontend frameworks such as React Angular or and backend technologies including RESTful APIs Django or Flask.
• Expertise in machine learning frameworks like PyTorch or Scikit-learn.
• Good experience with Generative AI models and techniques such as GANs or transformers.
• Good experience with OpenAI bedrock models cognitive services etc.
• Experience with cloud platforms like AWS Azure or Google Cloud specifically in deploying AI/ML applications.
• Strong understanding of databases such as SQL NoSQL and data warehousing solutions like Snowflake.
• Excellent problem-solving skills and the ability to work in a fast-paced collaborative environment.
• Experience with DevOps practices and tools for continuous integration and deployment (CI/CD).
• Knowledge of microservices architectures and containerization tools like Docker and Kubernetes.
• Familiarity with version control systems such as Git etc.
• Establish and make sure development standards security protocols and compliance requirements across custom engineering projects.
• Conduct regular code reviews performance evaluations and audits to ensure the integrity and reliability of delivered solutions.
• Collaborate with IT governance teams to ensure alignment to interpersonal policies and standards.

Desirable Skills/Experience:

• Experience in enterprise-level integrations and data engineering projects.
• Familiarity with data visualization tools such as Tableau or Power BI

When we put unexpected teams in the same room we unleash ambitious thinking with the power to inspire life-changing -person working gives us the platform we need to connect work at pace and challenge perceptions. Thats why we work on average a minimum of three days per week from the office. But that doesnt mean were not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

Why AstraZeneca:

Here engineering talent meets scientific purpose. You will work with advanced platforms real-world data and ambitious collaborators to deliver AI capabilities that tangibly speed research sharpen decision-making and expand access for patients. Backed by meaningful investment and a bold digital vision we pair high standards with freedom to experimentthink hackathons rapid pilots and scaling what worksso you can build learn and lead. We value kindness alongside ambition encourage transparent debate and bring diverse expertise together to solve problems that matter at global scale.

Call to Action:

Lead the next wave of AI application engineering that moves medicines to patients fastersubmit your application and start creating impact this quarter.

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.