Role overview
Join a collaborative, forward-thinking team building a next-generation agentic AI research assistant platform for the Life Sciences. This is an evolving multi-agent system that integrates multiple structured and unstructured data sources.
The focus is twofold:
- You will be tasked with the platform architect to solve specific technical and
architectural problems. You will have the ability to conduct research and
technical evaluation of issues relating to AgentCore, MCP, Agent to Agent
interactions and the general Agentic context, and to feed back and make
recommendations based on this.
- Building robust, production-ready backend services that integrate with APIs,
external data feeds, and orchestration layers.
The environment is only suitable for engineers who thrive on ownership, clean design, and real-world impact. You will only succeed if you are proactive, are able to think through tasks and deliver them confidently, and are willing to dive into, learn, and be excited about the domain. Curiosity, proactive thinking and strong engineering skills are essential.
What you'll work on
- You will be tasked with the platform architect to solve specific technical and
architectural problems. You will have the ability to conduct research and
technical evaluation of issues relating to Agentcore, MCP, Agent to Agent
interactions and the general Agentic context, and to feed back and make
recommendations based on this
- Design, develop, and maintain backend services and APIs using Python (FastAPI or
similar)
Integrate external data sources and APIs into the orchestration platform
Write clean, testable, and modular code with strong focus on unit and functional
testing
- Contribute to system design and architecture, particularly for integration and data
flow
- Collaborate with frontend developers, DevOps, QA, and other engineers in an Agile
environment
- Work independently on assigned features and take ownership of design,
implementation, and testing
- Participate in regular code reviews and Agile ceremonies
What we're looking for
- Awareness of LangGraph, LangChain, or other agentic/LLM orchestration
frameworks
Experience and knowledge of MCP
Experience with containerisation (Docker), CI/CD pipelines, or deployment workflows
Understanding of observability and monitoring practices
Experience working with knowledge graphs or structured document pipelines