Own end-to-end GenAI/AgenticAI lifecycle from concept to monitoring.
Design scalable AI systems: time-series, signals, LLMs/embeddings, orchestration, ML/DL.
Build and optimize production-grade LLM pipelines: RAG, embeddings, multi-agent workflows.
Architect AgenticAI apps using sensor data, unstructured text, and ML systems.
Develop Python backends/APIs to support AI agents and streaming data (Kafka/NSQ).
Drive engineering excellence via architecture discussions, code reviews, and technical leadership.

🎯 Requirements

4+ years in Data Science/ML/GenAI including production apps.
Hands-on production GenAI/AgenticAI experience.
Strong LLMs, prompting techniques, embeddings and vector DBs, RAG, agents, evals.
Experience with PyTorch, TensorFlow, Hugging Face, LangChain, CrewAI.
Strong Python across model dev, backend services, deployment, monitoring.
Familiar with streaming infra, Agile, distributed teams, cost optimization.

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