About UsData Oriented Defence Operations (DODO OÜ) is a cutting-edge Cybersecurity boutique based in Tallinn, Estonia. We operate at the absolute forefront of the Deep Tech industry, and yes, it's time to say it openly: we proudly emerged from the NATO ecosystem! We specialize in advanced Defence and Security solutions, pushing the boundaries of what is possible in autonomous offensive security.
The RoleWe are looking for a brilliant Python AI Engineer (Intern / Junior) to join our development team. You will be working on ARES, our autonomous red-teaming platform powered by Agentic AI.
In this crucial phase of product development, we are looking for a highly motivated talent (a Master's degree student or recent graduate) who wants to get hands-on with a complex, innovative agentic AI infrastructure. You won't be left to figure things out on your own: you'll be closely followed and mentored by cutting-edge profiles in AI and Cybersecurity Operations, ensuring a steep, hands-on, and highly rewarding learning curve.
What You Will Do- Agentic Backend Development: Design and optimize agent architectures using LangChain and LangGraph, supporting our CTO and the engineering team.
- Agentic RAG Pipelines: Build retrieval-augmented generation pipelines that let agents dynamically query knowledge bases, vulnerability databases, and prior engagement data to inform autonomous decision-making.
- Observability & Evaluation: Instrument agent pipelines with Langfuse for tracing, evaluation, and debugging of autonomous agent behavior.
- Structured Data & Validation: Use Pydantic to define robust schemas for agent inputs/outputs, tool calls, and inter-agent communication.
- Memory & State Systems: Build and maintain memory layers (vector stores, relational/database-backed memory) that let agents persist context across sessions and tasks, and feed retrieval pipelines.
- Target & Vulnerable Environment Creation: Build automated scenarios and vulnerable targets that our offensive AI will attack during QA and UAT phases.
- Cross-functional Bridging: Act as a technical bridge between the Agentic AI development team and the operational Cybersecurity team for test integration.
What We Are Looking For- Currently enrolled in a Master's degree program in Computer Science, Cybersecurity, AI, or a related field, or a Junior profile with early hands-on experience.
- Excellent proficiency in Python.
- Hands-on familiarity (coursework, projects, or professional) with LangChain, LangGraph, and/or agent-orchestration frameworks.
- Understanding of RAG (Retrieval-Augmented Generation) architectures — embeddings, chunking strategies, vector similarity search, and retrieval-grounded generation.
- Understanding of Pydantic (or similar) for data validation/schema design.
- Exposure to LLM observability/eval tooling (Langfuse or equivalent) is a strong plus.
- Comfort working with databases and memory/state persistence patterns for stateful applications.
- A genuine interest in offensive security, cloud architectures, and applied Artificial Intelligence.
- Ability to work autonomously on goal-oriented tasks (Full Remote environment).
What We Offer- 100% Full-Remote Environment: Operate from wherever you feel most productive.
- Tailored Compensation: Competitive, based on your experience and skill level.
- Expert Mentorship: Daily collaboration with top-tier industry experts in AI and Cyber Operations.
- Deep Tech Impact: Direct involvement in a Deep Tech project within the Defence and Security sector, with tangible impact on our technology roadmap.
- Career Growth: Concrete opportunity for position consolidation post-internship or evolution into key architectural roles as we scale.
If you want to build the future of autonomous cybersecurity, apply by sending your CV!
