Engenharia de IA SR (Agentes de IA)
New
J
JobgetherArtificial Intelligence
BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- GCPLLMGenerative AILangChain
Requirements
- Practical experience building AI agents and applications powered by Large Language Models, with the ability to take solutions from experimentation through production.
- Knowledge of agent frameworks and ecosystems such as ADK, LangGraph, LangChain, CrewAI, or similar technologies.
- Strong knowledge of the Google Cloud ecosystem, including Gemini Enterprise, Vertex AI, and related services.
- Solid understanding of Generative AI concepts, RAG, model evaluation, prompt engineering, memory, tools, and agent orchestration.
- Experience integrating APIs, events, microservices, and distributed architectures, combined with strong software engineering practices applied to AI solution development.
- Experience with LLMOps, AgentOps, observability, and governance practices for AI applications operating in production.
- Strong analytical and problem-solving skills, with the ability to collaborate effectively across Engineering, Architecture, and Business teams and translate complex challenges into scalable AI solutions.
Responsibilities
- Build, evolve, and industrialize AI agents, ensuring that solutions are scalable, secure, observable, and aligned with appropriate governance practices.
- Develop components, capabilities, and services that support a corporate Generative AI platform and enable the adoption of AI across different business use cases.
- Design architectures for AI agents, intelligent workflows, and LLM-based solutions, selecting appropriate technologies and patterns for each application.
- Develop prompting strategies and approaches for agent evaluation, optimization, memory, tool usage, and orchestration to improve solution quality and performance.
- Integrate AI agents and applications with APIs, internal systems, enterprise tools, events, and distributed architectures.
- Lead proofs of concept, pilots, and AI initiatives from initial experimentation through implementation and operation in production environments.
- Identify opportunities to automate and transform business processes through Generative AI while partnering with Engineering, Architecture, and Business teams to accelerate adoption and generate value.
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