Key Responsibilities:

- Design, develop, and deploy AI-powered solutions leveraging Machine Learning, NLP, Generative AI, RAG, and Agentic AI techniques.

- Translate business problems into prototypes, MVPs, and scalable production-ready solutions.

- Develop reusable AI frameworks, components, and accelerators that enable adoption across products and teams.

- Apply an AI-first mindset to identify opportunities for intelligent automation, workflow optimization, and business value creation.

- Partner with Product, Engineering, Content, and Business teams to deliver impactful customer outcomes.

- Drive delivery through agile ways of working, balancing experimentation, speed, and engineering quality.

- Communicate insights, innovation outcomes, and business impact through effective data storytelling and stakeholder engagement.

- Mentor team members and contribute to knowledge sharing, innovation forums, and AI.

Required Skills & Qualifications:

- Experience in Data Science, Machine Learning, NLP, Applied AI, or AI Product Development.

- Proven track record of delivering AI solutions from experimentation through production deployment.

- Experience working within product-focused, cross-functional teams.

- Demonstrated ability to independently solve complex problems and deliver measurable business outcomes.

Technical Skills:

- Strong expertise in Python and the modern Data Science ecosystem.

- Hands-on experience with Machine Learning, Deep Learning, NLP, and Statistical Modelling.

- Experience developing Generative AI applications using LLMs and modern AI frameworks.

- Strong understanding of RAG architectures, prompt engineering, embeddings, semantic retrieval, and vector databases.

- Exposure to Agentic AI and frameworks such as LangGraph, LangChain, CrewAI, AutoGen, or similar technologies.

- Strong SQL and data engineering fundamentals.

- Experience building APIs and intelligent services using FastAPI or similar frameworks.

- Familiarity with Git, Docker, CI/CD, cloud platforms (Azure and/or AWS), and MLOps practices.

- Strong Computer Science fundamentals including data structures, algorithms, system design, and software architecture principles.

We are looking for individuals who:

- Demonstrate a Go-Getter mindset with strong ownership, accountability, and a bias for action.

- Thrive in a builder culture, rapidly progressing from idea to prototype, MVP, and scalable solutions.

- Embrace a fail-fast, learn-faster approach while maintaining high engineering and delivery standards.

- Build trusted relationships and influence outcomes through strong collaboration with business, product, and technology partners.

- Adapt quickly to changing priorities, emerging technologies, and evolving business needs.

- Apply an AI-first mindset to reimagine workflows, automate processes, and unlock business value.

- Communicate complex technical concepts through compelling data storytelling and clear business narratives.

- Articulate customer, operational, and commercial impact, helping drive adoption and scale of innovative solutions.

- Actively contribute to the Data Science community through knowledge sharing, collaboration, and continuous learning.