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GenAI Engineer
GenAI Engineer
As a GenAI Engineer at Privado AI, you will develop interactive AI agents to perform privacy auditing tasks across web and mobile applications. This role involves building end-to-end audit agents, implementing consent verification workflows, integrating with various tools, and ensuring the reliability and scalability of compliance outputs.
About the role
About the Role
You will build interactive AI agents that execute privacy auditing tasks across websites and iOS/Android apps. These agents will plan and run audits, integrate with tools, collect evidence, and produce actionable compliance outputs reliably and at scale.
Responsibilities
- Build task-completing agents that run end-to-end audits: plan, execute, observe, iterate, and finish with clear completion criteria and safe fallbacks.
- Implement consent verification workflows (accept, reject, no action) and validate how tracking behavior changes across configurations and locations.
- Integrate agents with tools and services to enable audit execution (scan runners, traffic inspection, evidence capture, and reporting pipelines).
- Implement stateful workflows with task tracking and durable state so audits can be resumed, compared across releases, and run continuously.
- Create evaluation and observability loops: scenario-based tests, regressions, tracing/logging, and production monitoring to improve reliability and completion rates.
- Collaborate with Product/Design to ship an interactive experience with progress, explanations, confirmations, and actionable outputs.
Requirements
- 1-3 years of software engineering experience; strong Python fundamentals.
- Hands-on experience building interactive AI agents that complete multi-step tasks (not just chat): tool use, workflow orchestration, and state/memory management.
- Experience integrating with APIs and services and building backend endpoints for long-running workflows.
- Experience testing and debugging agent behavior using evaluations and runtime observability.
- Understanding of data structures, algorithms, and software design principles.
- Familiarity with production delivery (Docker, CI/CD, cloud basics).
Tech Stack (What You Will Use)
- Agent orchestration: LangGraph/LangChain (plus exposure to LlamaIndex, AutoGen, CrewAI, Semantic Kernel, Haystack, or similar).
- Backend: Python (Flask/Django).
- Frontend (helpful): React.
- Integrations/services (helpful): Node.js.
- Data stores: MongoDB (plus durable workflow/state storage as needed).
Nice To Have
- Multi-agent patterns (parallel specialists, coordination, routing).
- Experience building evidence-grade reports (reproducible outputs, clear pass/fail logic, traceability).
- Interest or exposure to privacy/compliance workflows (consent validation, tracking governance, third-party data flow visibility).
- Open-source contributions to agent tooling or developer platforms.