Senior Artificial Intelligence Engineer

Description

Job Summary: We are seeking a Senior AI Engineer to work embedded in business units, developing on-demand AI solutions and connecting business needs with the data team. Key Highlights: 1. Development of autonomous and conversational agents using various LLMs. 2. Acting as a bridge between business areas and the data team. 3. Implementation of advanced RAG techniques and integration of agents via APIs. We are looking for a Senior AI Engineer to be embedded within our client's business units, developing targeted, on-demand AI solutions with support from the internal data team. The professional will be responsible for transforming business unit requirements into functional intelligent agents—from conception through delivery. They will act as a bridge between business units and the data team, responsible for understanding each unit’s challenges, proposing AI-based solutions, and executing them end-to-end. **Responsibilities** * Develop autonomous agents using frameworks such as Agno, combining multiple tools into intelligent workflows. * Create conversational agents with short- and long-term memory, traceability, and personalization. * Experiment with and integrate various LLMs (OpenAI, Gemini, DeepSeek, etc.), evaluating performance vs. cost trade-offs for each use case. * Structure and optimize vector databases (ChromaDB, FAISS) and implement advanced RAG techniques connected to Snowflake and internal systems. * Implement intelligent data extraction via web scraping (Crawl4AI) and parsing of complex documents (Docling, Textract). * Integrate agents with internal APIs to autonomously perform tasks and update systems. * Maintain engineering best practices: clean code, version control, and documentation enabling seamless handover to the internal team. **Requirements** * Proficiency in Python and AI-focused libraries (Transformers, LangChain/Agno/LlamaIndex, scikit-learn, etc.). * Experience with autonomous agent frameworks and tool-augmented architectures. * Experience with AWS tools: S3, Lambda, ECR, SQS, Textract, EventBridge. * Hands-on experience integrating commercial LLMs into production applications. * Experience with APIs (requests, FastAPI), data manipulation, and database connectivity. * Experience with vector databases for semantic search and RAG. * Experience with Docker. * Version control best practices (GitHub) and architecture of scalable solutions. * Knowledge of LLM deployment in production and prompt engineering. **Preferred Qualifications** * Experience in Machine Learning (supervised, unsupervised, and reinforcement learning). * Experience with MLOps and automation of the model lifecycle. * Knowledge of LLM optimization. * Experience with conversational AI integrated with WhatsApp. ### **Required Knowledge and Skills:** Python, autonomous agent frameworks, AWS tools, S3, Lambda, SQS, Textract, EventBridge, LLMs, APIs, data manipulation, RAG, vector databases, Docker, GitHub, LLM deployment, prompt engineering ### **Benefits:** Childcare Assistance, Remote Work Allowance, Totalpass, Education Assistance, Birthday Day Off, Health Insurance, Dental Insurance, Life Insurance, Flexible Meal Voucher, Transportation Voucher ### **Department:** Growth & Digital Strategy