AI Engineer - Generative AI & AWS
New
Brazil, Aligned with U.S. business hoursContractSenior
Salary not disclosed
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Job Details
- Languages
- Advanced English and Spanish
- Experience
- 3+ years
- Required Skills
- AWSDockerPythonGitKubernetesCI/CDLLMGenerative AILangChain
Requirements
- 3+ years of experience in Software Engineering, AI Engineering, Machine Learning Engineering, or Cloud Engineering roles.
- At least 2+ years of hands-on experience with Generative AI, LLMs, or AI Agent frameworks.
- Strong proficiency in Python for backend development and AI system integration.
- Proven experience building and integrating APIs in production environments.
- Hands-on experience with AWS cloud services and infrastructure.
- Familiarity with LLM ecosystems such as OpenAI, Claude, Llama, or AWS Bedrock.
- Experience with AI orchestration tools such as LangChain, LangGraph, CrewAI, AutoGen, or similar.
- Solid understanding of RAG architectures and vector databases.
- Experience with CI/CD pipelines, Docker, and Kubernetes.
- Strong knowledge of Git and modern software development workflows.
- Advanced English and Spanish communication skills.
- Availability to work aligned with U.S. business hours from Latin America.
- Strong problem-solving mindset with the ability to work independently in complex environments.
Responsibilities
- Design, develop, and deploy Generative AI solutions leveraging Large Language Models and modern AI frameworks.
- Build and maintain AI Agent workflows, orchestration pipelines, and LLM-based applications for business use cases.
- Develop and integrate APIs using Python to connect AI systems with internal and external platforms.
- Architect and manage cloud-based AI infrastructure on AWS, ensuring scalability, security, and reliability.
- Implement and support production-ready AI applications using CI/CD pipelines, Docker, and Kubernetes.
- Work with vector databases, RAG pipelines, embeddings, and retrieval strategies to enhance AI system performance.
- Collaborate with technical teams and stakeholders to gather requirements and deliver robust AI-driven solutions.
- Participate in technical discussions, solution design, and client-facing communications when required.
- Troubleshoot, optimize, and continuously improve deployed AI systems and workflows.
- Contribute to engineering best practices, documentation, and system observability.
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