Senior AI Engineer – LLMs, Intelligent Agents
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Job Description
AI Engineer focused on LLMs and intelligent agents at Grupo SysMap. Designing and implementing AI solutions for various business sectors.
Responsibilities:
- Design, develop, and implement Artificial Intelligence solutions focused on LLMs, intelligent agents and RAG (Retrieval-Augmented Generation) architectures;
- Build, orchestrate and evolve AI agents for process automation, decision support and operational efficiency gains;
- Develop and structure backends, APIs and services required to support AI applications in production;
- Integrate AI models with enterprise systems, databases (SQL/NoSQL), file stores and external services;
- Create and maintain data and context pipelines, ensuring quality, traceability and relevance of information used by models;
- Evaluate, test and optimize performance, cost, scalability and solution quality of AI systems;
- Ensure best practices in security, governance and responsible AI usage, considering technical and regulatory risks;
- Collaborate with business teams to understand real problems and translate challenges into practical AI solutions;
- Occasionally develop simple interfaces or support frontend teams in integrating AI solutions;
- Provide technical leadership for initiatives, supporting team growth, dissemination of best practices and technical decision-making.
Requirements:
- Strong experience in Python development;
- Hands-on experience with LLMs (e.g., OpenAI, open-source models, etc.);
- Experience building AI agents and automated workflows;
- Knowledge of RAG architectures and use of embeddings;
- Experience integrating APIs and systems;
- Familiarity with databases (SQL and/or NoSQL);
- Experience with code versioning (Git) and software engineering best practices;
- Ability to work autonomously and provide technical leadership for deliveries;
- Experience with agent frameworks (LangChain, LlamaIndex, etc.);
- Experience with vector databases (Pinecone, Weaviate, FAISS, etc.);
- Experience in cloud environments (AWS, Azure or GCP);
- Knowledge of MLOps / LLMOps;
- Experience deploying and monitoring AI applications in production;
- Experience in intelligent automation projects or corporate copilots.
Benefits:
- Position also open to candidates with disabilities (PwD)
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