Frost & Sullivan MetaBrain Early Careers Program – AI Solution Architecture Internship

Launch Your Career with Frost & Sullivan At Frost & Sullivan, we believe that the future belongs to curious minds, innovative thinkers, and problem-solvers who are eager to make an impact. We are inviting applications from postgraduate students, recent graduates, and early-career professionals with up to two years of experience to join our growing global teams across various business, technology, research, consulting, AI, data, and corporate functions.

The Opportunity Frost & Sullivan is looking for intern roles supporting Meta. Brain. The work combines applied AI, business understanding, structured knowledge, quantitative models and trustworthy engineering to transform research and advisory into reusable software-enabled services. Build more than a demonstration. Work with industry researchers, advisors and engineers to turn AI capability into tested decision-intelligence software that enterprises can use.

Role Overview Show how your technical work supports a business problem. Research, consulting or advisory experience is preferred but not mandatory. Academic projects, thesis and reproducible research implementations are valid evidence; internships do not require prior full-time employment. Translate a business decision into an AI-enabled solution that can be tested, integrated and operated.

Work with Frost domain experts to connect research methods, knowledge structures, data, reasoning workflows and client-facing experiences. Proposed engagement Stipend: Yes, paid internship. Duration: Preferably six months, possibility of an extension up to 12 months based on performance and where academic arrangements and work authorization permits are in place.

Full-time Conversion: Depends on assessed performance, a suitable vacancy and eligibility; it is not guaranteed. Essential requirements Currently pursuing or holding a Master's or PhD in AI, machine learning, computer science, data science or a closely related field with substantial AI work. Strong Python, APIs, data structures and software-engineering fundamentals.

One demonstrable end-to-end AI prototype or research implementation, with clear individual contribution. Ability to explain how a model supports a business decision. Preferred: Knowledge graphs, information retrieval, agent workflows, enterprise integration, cloud services, user-experience design or applied business projects.

Research or consulting exposure is advantageous, not mandatory; production experience is not required for interns.

Key responsibilities

Join discovery and document the user, decision, alternatives, constraints and success measure. Translate an advisory brief into Input-Process-Output specifications, acceptance tests and a scoped backlog. Prototype the architecture: Design structured knowledge representations and retrieval grounded in approved sources.

Connect model outputs to deterministic calculations, APIs and tools; implement constrained workflows with clear human-review points. Evaluate the whole system: Compare retrieval and orchestration designs; measure factual support, task completion, latency and operating cost. Test failure handling and access boundaries and explain architecture choices to both business and engineering mentors.

Prepare for reuse: Create configuration schemas, interfaces, automated tests and architecture records. Contribute to advisor Design/Tuning and client Advisory/Simulation experiences; document handover, deployment assumptions and observability.