About Toptal

Toptal is a global network of top talent in business, design, and technology that enables companies to scale their teams on demand. With $200+ million in annual revenue and team members based around the globe, Toptal is the world’s largest fully remote workforce.

We take the best elements of virtual teams and combine them with a support structure that encourages innovation, social interaction, and fun. We see no borders, move at a fast pace, and are never afraid to break the mold.

About the client

Our client is a leading global consulting firm that delivers transformation programs for companies worldwide. They develop internal tools and client-facing web applications using modern full-stack development and Generative AI, focusing on automation, smarter decision-making, and enhanced user experiences.

About the role

We’re hiring Full-Stack Engineers (Python/React/GenAI) to join multiple production AI initiatives. You will collaborate with a multidisciplinary consulting team to build scalable web applications and integrate GenAI capabilities into business workflows.

This role is a great fit for engineers who like owning features end-to-end, collaborating with stakeholders, and shipping in a fast-moving environment. It’s also important to note: general full-stack experience alone isn’t enough. You’ll be expected to contribute both to new builds from scratch and to improving and expanding existing systems — including integrating GenAI features that will be used in production.

What success looks like:

Ship production-grade features end-to-end using Python (Django preferred) and React, including well-structured APIs and reliable deployments.
Deliver GenAI features in production (LLM interactions, workflow automation, data enrichment, RAG) with practical guardrails and evaluation.
Improve performance and maintainability by identifying bottlenecks, strengthening service boundaries, and contributing to CI/CD quality.
Collaborate effectively with distributed, cross-functional teams across multiple initiatives and geographies.

Responsibilities:

Develop, maintain, and optimize backend services using Python (Django preferred; Flask/FastAPI acceptable).
Build responsive, maintainable front-end interfaces using React.
Integrate Generative AI capabilities into existing and new applications (e.g., LLM interactions, workflow automation, data enrichment, RAG).
Design and implement REST APIs that connect front-end, back-end, and AI services.
Assist in testing, debugging, and deployment using modern CI/CD practices.
Collaborate with stakeholders to translate requirements into scalable, production-ready solutions.

Must have:

Experience of at least 3 years in the domain.
Solid hands-on understanding of Python (Django/Flask/FastAPI or similar).
High level of front-end familiarity with React (production web apps).
Hands-on experience building or integrating GenAI solutions in production (OpenAI/Azure OpenAI, LangChain, embeddings, vector DB, RAG).
Master the fundamentals of RESTful API/Service integration design.
Experience with databases: SQL and/or NoSQL.
Knowledge of cloud environments: AWS, Azure, or GCP.

Nice to have:

Knowledge of MLOps workflows (model evaluation, monitoring, prompt/versioning, deployment patterns).
Experience in consulting or enterprise settings.

Important to note:

Location: Brazil-based candidates ONLY (São Paulo & Rio areas)
Work model: Remote, with expected onsite visits a few times per month.
Type: Contract, 40h/week.
Duration: 6-12 months initially, with long-term engagement.
Authorization: Applicants must be authorized to work in their country of residence without employer sponsorship.

Why consider this opportunity?

You’ll get access to Toptal’s global network, including opportunities with Fortune 500 and other enterprise clients.
You’ll have flexibility to choose projects that match your goals — part-time or full-time, short-term or long-term (based on matching and availability).
There’s a potential path to direct employment with the client later.
The client may provide a Windows laptop.

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