AI Engineer

• Design and develop end-to-end NLP pipelines, from classical text processing to LLM-powered architectures
• Build and maintain systems for intent detection, NER, entity extraction, and text classification
• Design and optimize Retrieval-Augmented Generation (RAG) systems, including chunking, vector stores, hybrid search, and re-ranking
• Work with embedding models for semantic search, document retrieval, and intent classification in contact center contexts
• Design and implement agentic architectures involving tool use, function calling, multi-step reasoning, and orchestration
• Develop memory and context management strategies for multi-turn interactions
• Evaluate and benchmark models for hallucination detection, faithfulness, latency, token costs, and ongoing performance
• Integrate AI components into scalable, production-ready microservices with low-latency inference pipelines
• Collaborate with product and engineering teams to design AI-powered features and drive platform innovation

• 1-3 years of experience in a Data Science, AI or NLP Engineer role
• Strong programming skills in Python and core Data Science & ML libraries (Pandas, scikit-learn, NLTK, spaCy, Gensim)
• Solid understanding of NLP fundamentals — word embeddings, NER, information extraction, intent classification, text similarity
• Experience building and delivering ML products in production environments
• Hands-on experience with LLMs in production (OpenAI, Anthropic, Mistral, LLaMA, Gemini, or equivalent)
• Familiarity with RAG pipelines
• Experience with vector databases (Pinecone, Weaviate, Qdrant, pgvector, etc.) and modern embedding models
• Understanding of context window management, token budgeting, and prompt design for multi-turn conversations
• Experience with LLM Observability and Monitoring
• Experience with LLM frameworks such as LangChain, LlamaIndex, or Hugging Face Transformers
• Experience with agentic frameworks, function calling, or structured outputs
• Exposure to voice AI pipelines or speech-to-text systems
• Comfortable with cloud infrastructure and ML deployment (AWS, GCP, or Azure)

• Competitive compensation package
• Health insurance
• Career growth opportunities
• Access to training, events, and conferences
• Remote First model
• Free coffee
• Arcade machines
• Rooftops & terraces
• Team events
• A lot of fun!