Especialista de engenharia
J
JobgetherSecurity & IT
BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- DockerJavaKubernetesSpring BootMicroservicesGenerative AI
Requirements
- Strong professional experience in software engineering, with advanced proficiency in Java 17+ and Spring Boot.
- Solid experience designing and developing microservices, REST APIs, and GraphQL services.
- Strong knowledge of automated testing using technologies such as JUnit and Mockito.
- Experience applying Design Patterns, SOLID principles, Clean Architecture, Domain-Driven Design (DDD), and Event-Driven Architecture.
- Practical experience with CI/CD tools and practices, including Jenkins and GitHub Actions.
- Hands-on experience with Docker and Kubernetes.
- Proven practical experience developing or integrating Generative AI solutions.
- Strong understanding of Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG).
- Experience designing or implementing AI Agents and familiarity with MCP (Model Context Protocol).
- Experience working with AI platforms and APIs such as OpenAI API, Azure OpenAI, or Amazon Bedrock.
- Familiarity with LangChain, LangGraph, or comparable AI application frameworks.
- Experience with embeddings and vector databases such as Pinecone, OpenSearch, pgvector, Weaviate, or ChromaDB.
- Knowledge of model fine-tuning and evaluation techniques when applicable.
- Understanding of Responsible AI principles, AI governance, security, and model evaluation.
Responsibilities
- Lead the technical development of Generative AI, Machine Learning, and intelligent product initiatives.
- Design scalable architectures for applications based on LLMs, Retrieval-Augmented Generation (RAG), AI Agents, and multimodal models.
- Develop Java-based applications and services integrated with AI and Machine Learning capabilities.
- Define and establish engineering standards, reusable components, and best practices for AI-powered applications.
- Integrate foundation models and AI services into existing products and platforms.
- Develop and evolve AI solutions with a focus on scalability, reliability, performance, and cost efficiency.
- Implement solutions involving RAG, embeddings, vector databases, prompt engineering, AI Agents, and related technologies.
- Evaluate emerging AI models, frameworks, APIs, and development approaches, identifying opportunities for practical adoption.
- Build proofs of concept to validate new AI capabilities and accelerate innovation.
- Ensure intelligent solutions meet appropriate requirements for security, governance, observability, and responsible AI.
- Collaborate with Architecture, Product, Data, and Engineering teams to translate business needs into robust technical solutions.
- Provide technical guidance and mentorship to engineers adopting AI capabilities across products.
- Contribute to the automation of business and engineering processes through AI.
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