Applied AI Engineer
Remote · Brazil
Job Summary
Applied AI Engineer based in Latin America to support a long-term project for a software development client in Atlanta, GA. Responsibilities include designing, developing, and maintaining AI-powered applications and workflows (agents, multi-agent systems, and RAG-based solutions); integrating LLMs and AI services into internal and client-facing products to improve engineering productivity, automation, and software quality; building AI tooling for code generation, testing, documentation, debugging, and developer enablement; developing evaluation, monitoring, and observability frameworks for AI systems (prompt quality, latency, reliability, hallucination tracking); implementing scalable AI pipelines and orchestration workflows using modern AI frameworks and cloud infrastructure; prototyping and rapidly iterating on AI-driven solutions with production readiness; optimizing prompt engineering, retrieval strategies, memory management, and context orchestration; ensuring AI systems follow security, privacy, and governance best practices; requirements include advanced English, 5+ years of Python, production AI experience, experience with LangChain/LangGraph/LlamaIndex/OpenAI/Anthropic, vector databases, API design, observability tools, cloud platforms (AWS/Azure), and Docker; bonus points for a Bachelor's in CS or related fields; compensation in USD; benefits include PTO; remote/work arrangement not explicitly specified beyond regional mention; hints indicate LATAM and United States as locations.
Required Qualifications
- Advanced level of English
- 5+ years of professional software engineering experience with strong Python development skills
- Hands-on experience building AI systems in production environments, including agents, agentic workflows, RAG pipelines, or LLM-powered applications
- Experience with modern AI frameworks and tooling such as LangChain, LangGraph, LlamaIndex, OpenAI APIs, Anthropic APIs, or similar ecosystems
- Solid understanding of vector databases, embeddings, semantic search, and retrieval architectures
- Experience designing APIs and backend services for AI-enabled applications
- Familiarity with AI evaluation, instrumentation, observability, and monitoring tools
- Experience with cloud platforms and production infrastructure (AWS, Azure)
- Strong knowledge of software engineering best practices, including testing, CI/CD, scalability, and maintainability
- Experience working with Docker and containerized deployments
- Bonus Points: Bachelor’s Degree in Computer Science, Systems Engineering or related fields
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