We are seeking a Data Scientist with deep technical expertise in large language models, autonomous agent design, and intelligent system orchestration. This role focuses on building self-directed, context-aware AI systems that can reason, learn, and interact with humans and software environments.

Key Responsibilities

Design and build Agentic AI architectures capable of autonomous task execution, reasoning, and planning.
Develop and optimize LLM-driven multi-agent systems that coordinate, collaborate, and adapt dynamically.
Implement retrieval-augmented generation (RAG) and memory-based reasoning pipelines for intelligent context use.
Conduct prompt engineering, few-shot learning, and reinforcement learning to fine-tune agent behavior.
Build and manage knowledge graphs, embedding databases, and semantic retrieval layers to power reasoning.
Architect data ingestion, context extraction, and interaction layers that enable AI agents to interface with real-world APIs, databases, and systems.
Lead experimentation, evaluation, and optimization cycles to improve agent accuracy, autonomy, and decision quality.
Collaborate with AI engineers and product teams to integrate agents into scalable production systems.

Technical Skills

Core AI & ML: Python, PyTorch, TensorFlow, JAX, transformers, LLM tuning, prompt optimization
Agentic Frameworks: LangChain, LlamaIndex, CrewAI, multi-agent orchestration
Data & Knowledge Systems: FAISS, Pinecone, Milvus, Neo4j, ArangoDB
Infrastructure: Docker, Kubernetes, AWS, GCP, Azure
Advanced Capabilities: Self-improving agents, meta-learning, AI alignment, explainability

What You Will Work On