AI Engineer

Jobtailor; São Paulo; Presencial; BRL 150 000 - 260 000; Tempo integral

Resumo da oferta

Jobtailor is seeking engineers to develop intelligent agents using Large Language Models and Generative AI, with a strong emphasis on RAG, embeddings, and vector databases. You will deploy scalable AI services on Kubernetes and collaborate closely with clients on consulting engagements to deliver secure, observable AI applications.

The role requires hands-on Python development, knowledge of LangChain/LangGraph/LlamaIndex, and experience with AI observability tools such as LangSmith, Promptfoo,

Qualificações

• Strong development experience with Python.
• Advanced knowledge of Generative AI and Large Language Models (LLMs).
• Experience developing intelligent agents using LangChain, LangGraph, or LlamaIndex.
• Experience implementing RAG (Retrieval-Augmented Generation) solutions, including embeddings, semantic search, and vector databases.
• Experience deploying applications on Kubernetes.
• Experience in consulting projects or direct client engagement.
• Experience with observability and evaluation tools for AI applications, such as LangSmith, Promptfoo, and Arize Phoenix.
• Knowledge of AI application security (AI Security).
• Experience in the financial sector is a plus.

Responsabilidades

• Develop intelligent agents using Large Language Models (LLMs) and Generative AI.
• Design and implement RAG-based solutions with embeddings, semantic search, and vector databases.
• Deploy and monitor AI apps on Kubernetes with a focus on scalability and security.
• Collaborate with clients on consulting projects to deliver AI solutions.

Conhecimentos

Python

Generative AI

Large Language Models (LLMs)

RAG (Retrieval-Augmented Generation)

Client engagement / consulting

Observability & evaluation

AI security awareness

Ferramentas

LangChain

LangGraph

LlamaIndex

Kubernetes

LangSmith

Promptfoo

Arize Phoenix

Descrição da oferta de emprego

• Develop intelligent agents using LLMs
• Design and implement applications based on Generative AI
• Develop solutions based on RAG (Retrieval-Augmented Generation)
• Design pipelines for document ingestion, indexing, and retrieval
• Integrate AI models with APIs and enterprise systems
• Develop tools and automations for intelligent agents
• Create tools for agents
• Ensure scalability, security, monitoring, and optimization of developed solutions
• Monitor cost, performance, and utilization of models

Requirements

• Strong development experience with Python
• Advanced knowledge of Generative AI and Large Language Models (LLMs)
• Experience developing intelligent agents using frameworks such as LangChain, LangGraph, or LlamaIndex
• Experience implementing RAG (Retrieval-Augmented Generation) solutions, including embeddings, semantic search, and vector databases
• Experience deploying applications on Kubernetes
• Experience in consulting projects or direct client engagement
• Experience with observability and evaluation tools for AI applications, such as LangSmith, Promptfoo, and Arize Phoenix
• Knowledge of AI application security (AI Security)
• Experience in the financial sector is a plus

Core Competencies

Demonstrates expertise in developing intelligent agents using Large Language Models (LLMs) and Generative AI, with a strong focus on implementing Retrieval-Augmented Generation (RAG) solutions and ensuring the scalability and security of AI applications.