ciandt - CI&T - [Job-30309] Ai Engineer, Brazil
Requirements
• Bachelor's Degree in Computer Science, Engineering, Applied Math, or related fields • Strong programming background in Python (or similar) with experience in GenAI frameworks and APIs • Daily use of Generative AI IDEs or environments • Proven experience in Prompt Engineering, Context Engineering, AI Steering, RAG, MCP (Model Context Protocol) and building agent workflows • Solid experience with LLMOps, structured Evals, and LLM observability/tracing tools • Proven knowledge of GenAI Security practices (guardrails, prompt injection mitigation) and secure data integration • Solid understanding of A2A (Agent to Agent) and ACP (Agent Coordination Protocol) • Experience in deploying AI-powered solutions across the product development lifecycle, from design to monitoring • Understanding of how to integrate short and long-term memory in agents • Strong communication skills in English, both technical and business-oriented • Exposure to cloud native environments • Ability to work independently and collaboratively in fast-paced environments • Knowledge of reasoning strategies (Chain of Thought, ReAct) • Experience with Agentic AI frameworks, autonomous agents and Multi-Agent Orchestration frameworks (e.g., LangGraph, CrewAI) • Hands-on experience with LLM optimisation, Fine-Tuning techniques, and production inference deployment • Experience developing custom MCP (Model Context Protocol) servers to connect agents with external tools and data • Experience designing and applying evals to validate LLM outputs • Experience with Knowledge Graphs, or hybrid RAG approaches • Experience monitoring AI systems for performance, accuracy, and cost • Collaboration is our superpower, diversity unites us, and excellence is our standard. • We value diverse identities and life experiences, fostering a diverse, inclusive, and safe work environment. We encourage applications from diverse and underrepresented groups to our job positions.
Responsibilities
• Translate product and engineering challenges into AI-driven solutions that enhance speed, quality, and outcomes • Build and deploy AI Agents with advanced reasoning, integrating memory, MCP, custom MCP servers, and A2A • Partner with product and engineering teams to embed AI, LLMOps, and observability into requirements, coding, testing, monitoring, and operations • Prototype, test, optimise, fine-tune, and scale AI solutions, balancing experimentation with production readiness and inference deployment • Design, run, and automate evals to test LLM outputs for quality, reliability, and safety • Implement security guardrails and robust data integration across agentic workflows to mitigate vulnerabilities • Support pre-sales and client discussions by demonstrating applied AI use cases and outcomes • Stay ahead of research and practice in GenAI and bring them into daily engineering practice • Communicate findings and trade-offs clearly to both technical teams and executives
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