AI Developer Specialist, Python – Generative AI
Zup Innovation
full-time
Posted on:
Location Type: Remote
Location: Brazil
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About the role
- Design, implement, and maintain end-to-end AI/ML solutions, from prototyping to production, including scalable pipelines for training, validation, deployment, and monitoring of models (ML and LLMs) in production environments.
- Integrate machine learning and generative AI models (LLMs, embeddings, RAG, diffusion) into systems and digital products, building APIs, microservices, and data pipelines to support intelligent applications.
- Apply advanced software engineering and AI knowledge to solve complex business challenges, ensuring high scalability, reliability, and performance of developed components.
- Lead the development and management of model CI/CD infrastructure, covering versioning, automated testing, evaluation workflows, and technical documentation.
- Collaborate with multidisciplinary teams (data scientists, engineers, product owners, and business stakeholders) to understand challenges, propose innovative solutions, and integrate deliverables into robust continuous integration and delivery pipelines.
- Participate in designing modern architectures (cloud-native, serverless, event-driven) for scalable, resilient, and secure AI applications, following industry best practices in moderation, security, and compliance.
- Monitor, evaluate, and optimize the performance of models and systems in production, designing, measuring, and assessing model outputs with standard and custom metrics aligned to business goals.
- Translate cutting-edge AI research into production-ready features, delivering robust and scalable components that integrate with larger systems.
- Support the dissemination of AI culture within the company by sharing knowledge and mentoring other developers.
Requirements
- Proven experience in software development with Python, focused on AI/ML applications, including integration and operationalization of models in production environments (APIs, microservices, pipelines).
- Hands-on experience with Machine Learning/Deep Learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn, Hugging Face) and generative models (LLMs, diffusion), embeddings, and RAG.
- Experience with MLOps platforms and pipelines, including building, operating, and automating workflows (e.g., Docker, Kubernetes, Terraform, MLflow, Airflow, Kubeflow), using feature stores, and monitoring models in production.
- Solid experience with CI/CD on AWS, using services such as SageMaker, EKS, Lambda, Step Functions, CodeBuild, CodePipeline, ECR, S3, and CloudWatch.
- Practical experience with AI agents, orchestrators, or agentic frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or equivalents.
- Knowledge of relational and non-relational databases, with desirable experience in vector databases (Pinecone, Weaviate, Milvus).
- Practice in prompt engineering for LLMs and generative AI.
- Familiarity with modern architectures (cloud-native, serverless).
- Analytical ability to solve complex problems and a systemic perspective.
Benefits
- Freedom to work from anywhere
- Flexible working hours
- Education allowance
- Dedicated career development platform
- Internal guilds and study/interest groups
- Health insurance
- Dental insurance
- Discounts on medication purchases
- 24/7 telemedicine
- Free online therapy
- Wellhub
- Extended maternity leave
- Extended paternity leave
- CAZ – Zuppers Support Center
- Meal and food vouchers
- Life insurance
- Transportation voucher
- Home office allowance
- Childcare allowance
- Mobile phone plan subsidy
- Profit-sharing and results-based bonuses
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
PythonMachine LearningDeep LearningTensorFlowPyTorchScikit-learnHugging FaceMLOpsCI/CDprompt engineering
Soft skills
analytical abilityproblem solvingcollaborationmentoringcommunication