AI Engineer (Senior)

Accountabilities: Lead the end-to-end development of AI-powered solutions, from architecture and technical design to implementation, testing, and production deployment, using an agentic SDLC approach. Design and build agentic AI architectures, including LLM integrations through APIs, Retrieval-Augmented Generation (RAG), tool orchestration, runtime frameworks, system prompts, and safety guardrails. Develop and maintain context data pipelines using internal data sources and vector databases to provide AI agents with reliable, relevant, and high-quality information. Build backend services and APIs using Python and develop user-facing applications with React. Create, customize, and share reusable AI development assets, including agents, skills, subagents, commands, and development harnesses, to improve engineering productivity. Evaluate and validate AI solutions through automated testing, evaluation frameworks (evals), and red-teaming practices to identify hallucinations, prompt injection vulnerabilities, and potential data leaks. Critically assess AI-generated code and outputs, ensuring they meet technical standards, quality expectations, and business requirements. Optimize token consumption and inference costs through effective context management, RAG strategies, and agent-call orchestration. Implement observability across applications and agent workflows to monitor performance, behavior, output quality, and operational costs. Act as a senior technical reference, leading complex technical discussions, reviewing code, and mentoring other engineers. Collaborate with AI Deployment Engineers and AI Orchestrators to ensure solutions are production-ready and delivery remains predictable. Apply ethical AI principles and ensure compliance with privacy, data security, and regulatory requirements. Support delivery continuity through clear technical documentation and effective knowledge transfer. Requirements Proven experience as a Senior AI Engineer, with a strong track record of building and deploying AI-powered applications in production environments. Strong backend development skills in Python, including APIs, services, and data processing. Solid frontend development experience with React. Hands-on experience developing LLM-powered applications, including prompt engineering, context engineering, RAG, tool orchestration, and multi-agent architectures. Experience working with vector databases and context data pipelines. Knowledge of AI evaluation methodologies, automated testing, probabilistic behavior assessment, and AI red-teaming practices. Practical experience using AI coding agents and developing custom agents, skills, or commands to accelerate software delivery. Strong software architecture and engineering fundamentals, including microservices, event-driven architectures, CI/CD, Test-Driven Development (TDD), and observability. Experience with code analysis, document processing, parsing, or text extraction solutions. Ability to provide technical leadership, conduct code reviews, solve complex engineering challenges, and mentor team members. Fluent English proficiency (B2 level or higher), both written and spoken. Strong analytical thinking, problem-solving abilities, and effective communication skills. Nice to have: Experience analyzing, maintaining, or modernizing legacy codebases, including COBOL, Java, .NET, or similar technologies. Knowledge of advanced RAG architectures and knowledge graphs. Familiarity with LLM observability and evaluation tools. Experience working with Microsoft Azure. Experience with model fine-tuning techniques. Previous experience in financial services, banking, or the mortgage industry. Benefits Health and dental insurance. Meal and food allowances. Childcare assistance. Extended paternity leave. Gym and wellness partnerships through Wellhub (Gympass) and TotalPass. Profit Sharing and Results Participation (PLR). Life insurance. Access to a continuous learning platform through CI&T University. Discount club with access to exclusive offers. Free online platform dedicated to physical, mental, and overall well-being. Pregnancy and responsible parenting courses. Partnerships with online learning platforms. Access to language learning programs. Additional health, wellness, and professional development initiatives. Inclusive workplace with dedicated well-being professionals, inclusion specialists, and affinity groups. Support and reasonable accommodations throughout the recruitment process for professionals with disabilities.