Senior AI Engineer
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Job Description
AI Engineer at Verity developing and maintaining intelligent agents focusing on performance and quality. Collaborating with the technical team to implement modern architectures and best practices.
Responsibilities:
- Develop, evolve, and maintain AI agents with a focus on practical execution, performance, and delivering business value.
- Work hands-on in building agents following modern architectures and standards defined by the technical team.
- Ensure agent intelligence and accuracy, develop Prompt Engineering techniques, implement RAG (semantic search) architectures and vector databases.
- Implement AI agents using Python as the primary language.
- Develop orchestration flows and state-control using LangChain and LangGraph.
- Apply agent architectures based on MCP (Model Context Protocol), ensuring modularity and standardization, or A2A.
- Build integrations with systems, APIs, and internal data sources.
- Develop prompts, tools, and decision chains for agents.
- Implement mechanisms for memory, context, and information retrieval.
- Work with vectorized databases for semantic search and contextualization.
- Perform testing, validation, debugging, and continuous improvement of agents.
- Follow architectural standards defined by the AI Technical Lead.
- Ensure quality, performance, and reliability of the agents.
- Contribute to the evolution of the architecture and reuse of components.
- Collaborate with the AI Technical Lead and the Project Lead.
- Support the enablement of use cases defined with the internal client.
- Fine-tune agents based on feedback, usage metrics, and continuous iteration.
Requirements:
- Python for AI agent development.
- Prompt Engineering to optimize agent responses, reasoning, and accuracy.
- LangChain and LangGraph for orchestration flows, state control, and decision making.
- RAG (Retrieval-Augmented Generation) architectures for semantic search and context retrieval.
- Vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma or similar).
- Agent architectures based on MCP (Model Context Protocol) and/or A2A (Agent-to-Agent).
- Integration with systems and APIs (REST, authentication, internal data sources).
- Testing, debugging, and technical validation of agents in development and production environments.
- Monitoring agent performance and reliability.
Benefits:
- Meal voucher
- Food allowance
- Home office allowance
- Health insurance
- Dental insurance
- Life insurance
- Discount partnerships
- Agreements with establishments and educational institutions
- Recurring agility trainings
- Alura Intervalor licenses
- Verity #VerityComVocê
- Viva Engage
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