Senior Artificial Intelligence Engineer

KEY RESPONSIBILITIES Build the agent architecture: specialist agents for explanation, memorization, and practice behind a single companion persona Build the routing layer that knows the student's context and calls the right specialist at the right time Build RAG over NCERT and curriculum content, tied to the concept hierarchy Make the companion teach well in Hinglish tone, empathy, and code-switching that sounds like a real teacher Own evaluation: is the explanation correct, is it pitched right, did the student actually learn — automated and human-inthe-loop Implement mastery scoring and the logic that decides what a student sees next Own guardrails and safety for a student-facing AI, and keep latency and cost in check at scale REQUIRED SKILLS 5+ years in applied ML or NLP Strong Python (PyTorch / TensorFlow / scikit-learn) Hands-on with LLMs: prompt engineering, RAG, embeddings, vector stores Built multi-agent or tool-using systems in production, not just demos Ability to design an eval suite, not just run one Cloud ML infrastructure (GCP Vertex AI preferred; SageMaker / Azure ML also fine) Experience taking ML systems from prototype to production NICE TO HAVE Education or tutoring products — knowledge tracing, mastery models, spaced repetition Indian language NLP and Hinglish code-switching Production experience with Gemini / Claude / GPT-class models Speech and voice AI (Whisper, Deepgram, TTS) Serving LLMs cheaply at scale — caching, routing, smaller models where they suffice