Senior AI Engineer - Technology
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Job Description
Senior AI Engineer responsible for developing multi-agent architectures and ensuring efficient customer interactions. Collaborating with cross-functional teams and optimizing AI models in production.
Responsibilities:
- Design the solution's multi-agent architecture, defining agent topology, orchestration strategies, intent routing, and state management across the customer journey
- Create and implement specialized agents, defining roles, tools, memory, context and handoff rules between agents at each step of the developed flow
- Develop and optimize prompts, policies and guardrails, ensuring consistent, safe behavior aligned with internal guidelines (protection against prompt injection, jailbreak and leakage of sensitive information)
- Define and operate evaluation metrics, creating automated testing pipelines and continuously monitoring performance, latency, cost per interaction and response quality
- Ensure data security and privacy by implementing access controls, anonymization and interaction traceability
- Manage the lifecycle of models and agents in production (versioning, controlled rollouts, drift monitoring and fallback strategies)
- Create and maintain technical documentation and engineering standards (agent contracts, prompt templates, operational runbooks and development guidelines)
- Collaborate with product, data and software engineering teams to ensure reliable integration of agents with other systems.
Requirements:
- Solid experience developing and deploying GenAI solutions in production (LLMs, RAG and autonomous agents)
- Proficiency in Python for AI engineering (agent orchestration, API integration, error handling and resilience)
- Experience with agent frameworks such as LangGraph and LangChain
- Hands-on experience with RAG (chunking, embeddings, vector indexing, reranking and context relevance evaluation)
- Experience evaluating LLMs (defining metrics, creating evaluation datasets)
- Knowledge of LLM security practices (prompt injection, jailbreak, output filtering, Llama Guard or equivalents)
- Experience with MLOps/LLMOps (experiment tracking, model versioning, production monitoring preferably with MLflow or similar)
- Knowledge of SQL and integration with structured data sources and REST APIs
- Experience within the Azure ecosystem.
Benefits:
- iFood voucher (meal allowance)
- Financial assistance
- Health insurance
- Dental insurance
- Birthday day off
- Life insurance
- Extended maternity and paternity leave
- Educational partnerships
- TotalPass partnership - health and wellness
- Clude Saúde partnership
- Reimbursement programs
- Flexible working hours
- Dress code: be yourself.
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