About the Role
Data Oriented Defence Operations (DODO OÜ) is a cutting edge Cybersecurity boutique based in Tallinn, Estonia. We operate at the forefront of Deep Tech, and yes, it's time to say it openly: we proudly emerged from the NATO ecosystem. We build advanced Defence and Security solutions and push the boundaries of autonomous offensive security. We are looking for a Python AI Engineer (Junior) to join our development team and work on ARES, our autonomous red teaming platform powered by Agentic AI.
Responsibilities
•Design and optimize agent architectures using LangChain and LangGraph, supporting our CTO and the engineering team
•Build retrieval augmented generation pipelines that let agents query knowledge bases, vulnerability databases, and prior engagement data to inform autonomous decisions
•Instrument agent pipelines with Langfuse for tracing, evaluation, and debugging of autonomous agent behavior
•Use Pydantic to define robust schemas for agent inputs and outputs, tool calls, and communication between agents
•Build and maintain memory layers (vector stores, relational and database backed memory) so agents keep context across sessions and tasks
•Build automated scenarios and vulnerable targets that our offensive AI attacks during QA and UAT phases
•Act as the technical bridge between the Agentic AI development team and the operational Cybersecurity team for test integration
Requirements
•Hands on experience building agentic AI systems: projects you've actually built and can talk us through, including the architecture you chose, what worked, and what you'd do differently today
•Practical experience with LangChain and LangGraph: structuring graphs, managing state across nodes, handling tool calling, and debugging agents that loop or stall
•Excellent Python
•Solid understanding of RAG: embeddings, chunking strategies, vector similarity search, and retrieval grounded generation, ideally with experience tuning a pipeline yourself
•Pydantic (or similar) for data validation and schema design
•Comfort with databases and state persistence patterns, both vector stores and relational or document stores
•Master's degree, enrolled or completed, in Computer Science, Cybersecurity, AI, or a related field
•Ability to work autonomously on goal oriented tasks in a fully remote setup, managing your own 22h per week
•Genuine interest in offensive security, cloud architectures, and applied AI
•Because of the nature of our work in Defence and Security, we can currently only consider candidates who hold European (EU/EEA) citizenship and live in Europe
Nice to Have
•Python backend experience: building and consuming APIs (FastAPI, Flask, or similar), async programming, and services that hold up in production
•Langfuse or similar LLM observability and evaluation tools
•Exposure to offensive security tooling, CTFs, or pentesting fundamentals
•Experience with multi agent orchestration patterns beyond LangGraph
•Familiarity with Docker and cloud deployment on any major provider
Conditions
•Paid 6 month engagement: €3,800 to €4,200 in total depending on experience, paid in two tranches. The first 3 months are a trial period
•100% fully remote, flexible part time (within Europe): about 22h per week, organized around your own schedule
•Expert Mentorship: Daily collaboration with top tier industry experts in AI and Cyber Operations
•Deep Tech Impact: Direct involvement in a Deep Tech project in Defence and Security, with real impact on our technology roadmap
•Career Growth: A path to a full time role with a stock option plan if the funding round closes, and growth into key architectural roles as we scale
