Applied AI Engineer

Applied AI Engineer

We are looking for an Applied AI Engineer based in Latin America to work on a long-term project for one of our clients, a Software Development company based in Atlanta, Georgia. Our client is building a secure, bank-grade AI infrastructure and developing cutting-edge applications designed to power the next generation of modern banking and financial services.

Responsibilities:

• Design, develop, and maintain AI-powered applications and workflows, including agents, multi-agent systems, and RAG-based solutions.
• Integrate LLMs and AI services into internal and client-facing products to improve engineering productivity, automation, and software quality.
• Build AI tooling for code generation, testing, documentation, debugging, and developer enablement.
• Develop evaluation, monitoring, and observability frameworks for AI systems, including prompt quality, latency, reliability, and hallucination tracking.
• Implement scalable AI pipelines and orchestration workflows using modern AI frameworks and cloud infrastructure.
• Prototype and rapidly iterate on AI-driven solutions while balancing experimentation with production readiness.
• Optimize prompt engineering, retrieval strategies, memory management, and context orchestration.
• Ensure AI systems follow security, privacy, and governance best practices.

Requirements:

• 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.

What we offer:

• Compensation in USD
• Paid time off
• Cool clients and products
• Work with great engineers