Senior AI Engineer
New
J
JobgetherGenerative AI
Based in BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- Significant professional experience in software engineering
- Required Skills
- PythonCI/CDPrompt EngineeringLLMLangChain
Requirements
- Significant professional experience in software engineering, ideally developing complex, production-grade applications.
- Full-stack development experience across backend services, APIs, and application integrations.
- Hands-on experience with LLMs, foundation models, and associated APIs.
- Practical experience designing and implementing agentic architectures using frameworks such as LangChain, LlamaIndex, CrewAI, or AutoGen.
- Strong knowledge of prompt engineering, prompt optimization, and techniques for improving LLM performance and output quality.
- Experience building retrieval and knowledge systems using vector databases such as Pinecone, Weaviate, or OpenSearch, along with embedding models or knowledge graphs.
- Proficiency in Python and familiarity with frameworks and libraries for AI-powered applications.
- Experience with cloud-based AI platforms, particularly AWS Bedrock; familiarity with the OpenAI SDK and Gemini.
- Understanding of DevOps practices, containerization, and CI/CD pipelines for deploying and maintaining AI applications.
- Ability to design scalable, maintainable, reliable AI systems that integrate with enterprise environments.
Responsibilities
- Design, develop, and deploy production-ready applications powered by LLMs and foundation models, including through AWS Bedrock.
- Architect, build, and optimize RAG pipelines for large-scale document repositories.
- Implement and orchestrate multi-agent AI systems using AWS Bedrock Agents, AgentCore, and agentic frameworks.
- Develop scalable AI pipelines and integrate them with enterprise systems.
- Build backend services and APIs for AI applications using Python and modern frameworks.
- Implement containerization, deployment strategies, and infrastructure practices for reliable delivery.
- Develop monitoring and observability solutions for AI performance, response quality, reliability, and costs.
- Design and refine prompts, evaluate and fine-tune models, and experiment with configurations and architectures.
- Collaborate with multidisciplinary teams and business stakeholders to translate requirements into technical solutions.
- Document engineering standards and best practices, assess emerging AI technologies, and contribute to sales-related generative AI initiatives.
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