AI Specialist Architect
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Job Description
AI Architect developing AI solutions utilizing LLMs and multi-agent systems at Stefanini. Focused on innovative problem-solving in global business transformations.
Responsibilities:
- Design and implement AI solutions leveraging LLMs, RAG and multi-agent systems, ensuring architectures meet specific business requirements and are scalable.
- Apply advanced RAG techniques to optimize search and information retrieval processes, using approaches such as multi-query, hybrid search, re-ranking and GraphRAG.
- Develop, orchestrate and manage specialized agents in multi-agent environments, using Agent-to-Agent (A2A) architectures to ensure effective communication and collaboration between agents.
- Integrate a variety of tools, data sources and agent capabilities using the Model Context Protocol (MCP), ensuring all system components communicate efficiently.
- Use AI-assisted development tools, such as Claude Code and Antigravity, to improve development efficiency and accelerate solution delivery.
- Drive Spec-Driven Development (SDD), converting business requirements into executable technical specifications that guide implementation.
- Work with vector databases such as Pinecone, ChromaDB, FAISS and Vertex AI Vector Search to store, manage and retrieve vector data efficiently.
- Implement and optimize embeddings, chunking and retrieval pipelines to ensure accurate and effective semantic search.
- Design and implement distributed systems that ensure high availability, resilience and scalability, integrating messaging solutions and observability for continuous monitoring.
- Develop and maintain backend applications, including API integrations to support AI workloads, ensuring solutions are robust and efficient.
- Apply advanced Python skills to build AI solutions, automate processes and integrate systems using relevant libraries and frameworks.
- Manage and implement solutions in cloud environments, preferably Google Cloud Platform (GCP), using services such as Vertex AI, BigQuery and Spanner.
- Act strategically and hands-on in defining architecture and engineering standards, collaborating with cross-functional teams to ensure delivery of high-quality solutions.
Requirements:
- Strong experience architecting AI solutions using LLMs, RAG and multi-agent systems.
- Advanced knowledge of modern RAG patterns, including multi-query, hybrid search, re-ranking and GraphRAG.
- Hands-on experience developing and orchestrating specialized agents and Agent-to-Agent (A2A) architectures.
- Proficiency with the Model Context Protocol (MCP) for integrating tools, data sources and agent capabilities.
- Experience with AI-assisted development tools (AI-Assisted Development), such as Claude Code, Antigravity or equivalents.
- Familiarity with Spec-Driven Development (SDD) and translating business requirements into executable technical specifications.
- Practical experience with vector databases such as Pinecone, ChromaDB, FAISS, Vertex AI Vector Search or equivalents.
- Solid understanding of embeddings, chunking, retrieval pipelines and semantic search.
- Strong experience with distributed systems, messaging, observability, resilience and scalability.
- Experience with backend development and API integration for AI workloads.
- Advanced Python knowledge applied to AI solutions and automation.
- Experience with cloud environments, preferably Google Cloud Platform (GCP).
- Ability to operate both strategically and hands-on in defining architecture and engineering standards.
Benefits:
- Meal allowance or meal voucher.
- Discounts on courses, universities and language institutions.
- Stefanini Academy — online platform with free, up-to-date courses and certificates.
- Mentoring.
- Benefits club for medical consultations and exams.
- Health insurance.
- Dental insurance.
- Discount and benefits club at top establishments.
- Travel club.
- Pet care partnership.
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