Principal AI Architect
Location: Bengaluru, India
Department: Software Product Management
Experience: 12+ Years
- Advanced machine learning and deep learning architecture
- Time-series and foundational forecasting models
- Demand forecasting, inventory forecasting, and retail planning models
- Model evaluation, benchmarking, drift detection, and monitoring
- Scalable ML system design and MLOps
- Retail demand planning, assortment, pricing, promotions, and inventory optimization
- Domain adaptation for retail-specific AI use cases
- Understanding of retail data: POS, inventory, promotions, pricing, loyalty, supply chain
- Forecast explainability and business-impact measurement
- LLM fine-tuning and domain adaptation
- Supervised Fine-Tuning, SFT
- RLHF / RLAIF workflows
- Prompt engineering and prompt evaluation
- Retrieval-Augmented Generation, RAG
- Agentic AI architecture
- Guardrails, hallucination reduction, and LLM safety
- End-to-end AI platform architecture
- Cloud-native AI systems on AWS, Azure, or GCP
- Distributed training and inference optimization
- Vector databases and semantic search
- Model serving, latency optimization, and cost optimization
- Data lakehouse / feature store architecture
- AI strategy and roadmap ownership
- Technical leadership for senior ML engineers and data scientists
- Cross-functional collaboration with product, engineering, and business teams
- Executive communication and solution storytelling
- Architecture governance and best-practice definition
- Python, PyTorch, TensorFlow
- Hugging Face, LangChain, LlamaIndex
- MLflow, Kubeflow, Airflow
- Databricks, Snowflake, Spark
- Kubernetes, Docker
- OpenAI, Anthropic, Gemini, open-source LLMs
- Vector DBs: Pinecone, Weaviate, FAISS, Milvus
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