About the role
We're looking for a Senior Full-Stack Engineer who can build large-scale, cloud-native systems and integrate Generative AI (LLMs, embeddings, vector DBs, RAG) into real-world security automation products. You'll design, develop, and scale high-performance SaaS features used globally by security teams handling millions of alerts per day.
Responsibilities:
- Architect and build major subsystems for the next-gen AI-driven security automation platform.
- Integrate GenAI components (LLMs, embeddings, vector DBs) into orchestration workflows for faster incident triage.
- Build intuitive APIs and AI-first integrations with third-party ecosystems.
- Develop natural-language interfaces, intelligent summarization, and auto-remediation features using GenAI.
- Convert AI/ML/GenAI proofs-of-concept into production-grade features.
- Drive engineering best practices across full-stack development, MLOps, testing, and responsible AI.
- Mentor junior engineers and collaborate with global cross-functional teams.
Requirements:
- 4-8 years of software development experience, with strong exposure to distributed systems.
- Strong in algorithms, data structures, system design, and architectural patterns.
- Hands-on expertise in C#/. NET Core, NodeJS, TypeScript, Angular, Python.
- Experience with SQL/NoSQL and vector databases.
- Proven experience building GenAI/LLM-based applications (prompt engineering, RAG, fine-tuning).
- Knowledge of real-time systems (WebSockets, SignalR).
- Strong AWS + Kubernetes + Terraform experience.
- Familiarity with MLOps pipelines and observability for GenAI systems.
- Excellent communication and collaboration skills.
Nice to Have:
- Cybersecurity or security automation experience.
- Experience with LLMOps, responsible AI, or AI governance.
- Open-source contributions in AI/GenAI.
Tech Stack:
- Backend: C#, . NET Core, Node.js, Python.
- Frontend: TypeScript, Angular.
- Databases: MongoDB, Postgres, MySQL, Vector DBs (Pinecone / Weaviate / Milvus).
- Cloud & Infra: AWS, Kubernetes, Terraform.
- AI/GenAI: LangChain, OpenAI/Anthropic APIs, Hugging Face, RAG pipelines, fine-tuning, MLOps.