AI Engineer

This is a fully remote position, open to applicants in Portugal.

📋 Description

• Create and implement comprehensive NLP pipelines — ranging from traditional text processing to cutting-edge LLM-driven architectures.

• Develop and sustain systems for intent detection, named entity recognition (NER), entity extraction, and text classification, both as standalone applications and as integral components within larger LLM workflows.

• Design and enhance Retrieval-Augmented Generation (RAG) systems — including chunking strategies, vector store architectures, hybrid search (dense + sparse), and re-ranking pipelines.

• Collaborate with embedding models for semantic search, document retrieval, and intent classification specifically in contact center environments.

• Develop and execute agentic architectures — incorporating tool use, function calling, multi-step reasoning, and orchestration using frameworks such as LangChain, LlamaIndex, or custom-built solutions.

• Create strategies for memory and context management — focusing on short-term conversation memory, long-term user context, and optimizing context windows for multi-turn interactions.

• Rigorously evaluate and benchmark models: including hallucination detection, faithfulness scoring, latency/token cost trade-offs, and continuous performance monitoring.

• Integrate AI components into scalable, production-ready microservices with an emphasis on low-latency inference pipelines.

• Work alongside product and engineering teams to conceptualize new AI-enhanced features and promote innovation throughout the platform.

⛳️ Requirements

• 1-3 years of experience in a Data Science, AI, or NLP Engineer position.

• Proficient programming skills in Python along with core Data Science and ML libraries (Pandas, scikit-learn, NLTK, spaCy, Gensim).

• Strong grasp of NLP fundamentals — including word embeddings, NER, information extraction, intent classification, and text similarity.

• Proven experience in building and delivering ML products in production settings.

• Practical experience with LLMs in production (OpenAI, Anthropic, Mistral, LLaMA, Gemini, or similar).

• Familiarity with RAG pipelines.

• Experience with vector databases (Pinecone, Weaviate, Qdrant, pgvector, etc.) and contemporary embedding models.

• Understanding of context window management, token budgeting, and prompt design for multi-turn conversations.

• Experience with LLM observability and monitoring.

• Familiarity with LLM frameworks such as LangChain, LlamaIndex, or Hugging Face Transformers.

• Bonus: Experience with agentic frameworks, function calling, or structured outputs.

• Bonus: Exposure to voice AI pipelines or speech-to-text systems.

• Bonus: Comfortable with cloud infrastructure and ML deployment (AWS, GCP, or Azure).

🏝️ Benefits

• Competitive compensation package.

• Health insurance.

• Career growth opportunities.

• Access to training, events, and conferences.

• Remote First model – and if you visit one of our offices, be prepared for: ☕ Free coffee | 🎮 Arcade machines | 🌇 Rooftops & terraces | 🎉 Team events | 😃 A lot of fun!