Job Summary

The Data Scientist Agentic AI Scientific Systems is a senior technical contributor responsible for designing, building, and integrating AI capabilities that accelerate scientific discovery across domains such as protein engineering, structure prediction, disease biology, and target identification.

This role focuses on developing agentic AI systems and scientific AI workflows that combine foundation models, domain-specific models, knowledge sources, and computational tools into reusable solutions that support scientific decision-making.

The engineer works closely with scientific domain leads to translate research needs into scalable AI solutions and reusable capabilities. This role serves as a bridge between scientific innovation and enterprise AI platforms, helping establish a foundation for next-generation AI-assisted scientific workflows.

Core Responsibilities Agentic AI Systems Development

Design and implement agent-based systems that support complex scientific workflows.

Develop capabilities including:

- Tool calling and tool orchestration
- Multi-step reasoning workflows
- Retrieval-augmented generation (RAG)
- Knowledge-grounded AI systems




- Human-in-the-loop decision workflows
- Multi-agent collaboration patterns

Build reusable components for:

- Agent orchestration
- Context management
- Memory and state handling
- Workflow planning and execution
- Scientific tool integration

Evaluate emerging agent frameworks and contribute to standards and best practices across projects.

Knowledge Systems Retrieval

Design and implement knowledge-driven AI systems that connect LLMs and agents with enterprise and scientific data.

Develop solutions utilizing:

- Vector databases
- Knowledge graphs
- Graph-RAG architectures
- Scientific literature and domain knowledge repositories

Ensure AI systems leverage authoritative knowledge sources and support traceability and explainability.

AI Workflow Engineering

Develop end-to-end workflows that combine:

- Data ingestion and preparation
- Knowledge retrieval
- Model inference
- Scientific analysis

Create reusable workflow patterns that can be applied across multiple scientific domains and projects.

📌 Data Scientist (Hyderabad)
🏢 Amgen
📍 Hyderabad