AI Engineering Expert
We are Reckitt
Information Technology & Digital
In IT and D, you'll be a force for good, whether you're championing cyber security, defining how we harness the power of technology to improve our business, or working with data to guide the innovation of consumer loved products.
Working globally across functions, you'll own your projects and process from start to finish, with the influence and visibility to achieve what needs to be done. And if you're willing to bring your ideas to the table, you'll get the support and investment to make them happen.
Your potential will never be wasted. You'll get the space and support to take your development to the next level. Every day, there will be opportunities to learn from peers and leaders through working on exciting, varied projects with real impact. And because our work spans so many different businesses, from Research and Product Development to Sales, you'll keep learning exciting new approaches.
About the role
Join our Global Data & Analytics team and embark on an exciting journey to unravel the hidden insights within vast data oceans. We're dedicated to empowering smarter decisions and delivering superior products to our global consumers and customers.
As an AI Engineering Expert you will play a crucial role in developing and deploying AI and GenAI solutions to support R&D Stream. This role combines technical leadership—guiding external teams and ensuring alignment with best practices—with hands-on delivery of AI-driven solutions. You will work closely with the platform team to align the tech stack with organizational standards while staying at the forefront of AI advancements. Your ability to seamlessly integrate AI into business workflows will be instrumental in transforming insights into tangible impact.
Your responsibilities
- Developing & Delivering GenAI Solutions: Lead the deployment and management of AI/GenAI capabilities, primarily leveraging existing APIs and third-party models, while ensuring practical and impactful integration into product concept creation.
- Technical Leadership & Cross-Team Coordination: Guide external teams in implementing AI solutions while collaborating with internal platform and engineering teams to align with organizational standards and ensure scalability, security, and efficiency.
- Stakeholder Engagement: Act as a key interface between R&D and the broader Data & Analytics ecosystem, translating business needs into AI-driven solutions and effectively communicating progress, challenges, and best practices.
- AI Technology & Best Practices: Stay ahead of GenAI advancements (e.g., Transformer architectures, large language models, MLOps), assessing and integrating new tools to enhance existing AI capabilities.
- Data Strategy & Infrastructure: Advocate for robust data foundations, working with data engineering teams to optimize data pipelines, storage, and processing, ensuring AI solutions are built on high-quality, well-structured data.
- Measurement & Optimization: Define KPIs, conduct experiments (e.g., A/B testing), and refine AI applications based on real-world performance to maximize their impact on product innovation and decision-making.
- Mentorship & Knowledge Sharing: Provide technical leadership, mentoring junior data scientists and analysts while fostering a collaborative, AI-driven culture within the Global Data Science Chapter.
The experience we're looking for
- Right Education: Master’s or PhD in a quantitative field (Computer Science, Data Science, Statistics, etc.).
- Technical Expertise:
- Strong experience developing GenAI applications using Python: hands-on experience with Large Language Models (LLMs), RAG architectures, embeddings, and prompt engineering.
- Strong software engineering fundamentals, including API development, testing, version control, and maintainable code design.
- Experience designing and deploying AI solutions in Azure cloud environments.
- Strong knowledge of SQL and data management principles, experience with Databricks is a plus.
- Familiarity with ML/LLMOps tooling, model evaluation, monitoring, and deployment practices (with e.g. LangFuse or MLflow)
- Domain Knowledge: Understanding of R&D process is an advantage.
- Leadership & Communication: Strong stakeholder management skills, with the ability to lead technical teams and bridge technical and business functions, effectively translating complex AI concepts for both technical and non-technical audiences.
- Adaptability: Comfortable working in a fast-paced environment with shifting priorities, ready to pivot as AI technologies evolve.
The skills for success
Digital Strategy, Product Solution Architecture, Data Governance, Product Compliance, Digital Transformation, Stakeholder Relationship Management, Outstanding Communication, stakeholder engagement, Innovation Processes, Innovation, User Experience Design.
What we offer
Equality
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