Senior Software Engineer, GenAI Security product (Vulcan)

We are seeking a Senior Software Engineer to be the technical heartbeat of our GenAI security capabilities. In this role, you sit at the exciting intersection of Research and Product, turning breakthrough experiments into scalable, production-grade software. You won’t just be implementing features; you’ll be designing the sophisticated tooling and AI Agent architectures that make the Vulcan Platform unique. We offer a playground for builders who want to solve unsolved problems, master advanced prompt engineering, and work alongside a world-class team. Come build the shield for the AI era and expand your technical horizons.

Learn more about us 👉

• Vulcan product: https://vulcanlab.ai/
• Vulcan LinkedIn: https://www.linkedin.com/company/vulcanlab-ai/
• AIFT group: https://aift.io/

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How to apply

Please apply with English CV through https://job-boards.greenhouse.io/aift/jobs/5744136004

Thank you.

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What you'll do

1. Core Application & Platform Development (Full Stack)

• Vulcan Platform: Partner with Product and Design to build intuitive frontend interfaces (React, Next.js) for dashboards, configuration consoles, and visualization tools.
• Backend Services & APIs:
  • Develop and maintain the essential APIs (FastAPI/Python) and microservices that power the Vulcan platform.
    
  • Architect robust task execution systems using Message Queues (Celery, RabbitMQ) to handle long-running asynchronous AI inference tasks.
    
• Internal Tooling Ecosystem: Build frontend and backend tools that accelerate internal teams (Project, ML/AI), including configuration panels, data visualization pipelines, and evaluation interfaces.
• Guardrails & Security Features: Implement backend services for AI guardrails (content moderation, prompt filtering) and automated adversarial testing pipelines.

2. GenAI Agent & Logic Engineering

• Prompt Engineering as Code: Treat prompts as software logic. Lead the design and implementation of AI Agent behaviors, optimizing responses through structured Prompt Engineering techniques.
• Agent Workflow Design: Orchestrate complex, multi-step LLM workflows where the "application logic" involves chaining model interactions effectively.
• Response Handling: Design robust parsing and validation mechanisms to ensure raw model outputs are converted into structured, usable application data. 

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• Professional Experience
  • 3+ years of total software development experience with a focus on web applications and backend systems.
  • Experience working in a development team of 3+ engineers
  • Familiar with collaborative development practices such as code reviews, issue tracking, and team-based delivery

• Technical Mastery
  • Full Stack Proficiency: Experienced in Backend and Frontend, with the ability to switch contexts effectively.
  • System Design: Solid understanding of System Design principles, specifically in building scalable web applications and microservices.
  • Engineering Mindset: You treat AI/LLMs as a software component. You focus on reliability, testing, and maintainability of the code surrounding the model.

• Soft Skills & Mindset
  • Independent Execution: Excellent ability to plan, organize, and execute features from concept to production with minimal supervision.
  • Cross-Functional Collaboration: Superior communication skills to translate requirements between AI/ML Researchers and non-technical stakeholders (PMs).
  • Fluent in Mandarin, basic proficiency in English (B1 level).

Nice-to-haves

• Leadership Experience: Proven experience leading an engineering team or mentoring junior engineers.
• Async Architecture: Deep familiarity with Task Executors and Message Queues (Celery, RabbitMQ) for high-concurrency workloads.
• LLMOps Tools: Experienced in tools like Langfuse, MLflow, or similar observability and evaluation platforms.
• CI/CD: Experienced in designing and maintaining CI/CD pipelines (e.g., GitLab CI) for automated testing and deployment.

Experience with these tools is a plus, but we value strong engineering fundamentals and learning ability over specific tool experience.

Tech Stack

• Core: Python, TypeScript
• Web: FastAPI, React, Next.js
• AI/Data Ops: Celery, RabbitMQ, PostgreSQL, Redis, MLflow, Langfuse

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• Phone interview: 1 hour meet with HR
• Technical Assignment: A take-home or online assessment focused on System Design & AI Integration.
• Onsite Interview (2-3 hours):
  • Meeting with the Engineering Teams & Hiring Managers to discuss architectural approaches and collaboration.
  • Technical deep-dive on AI and software engineering standards.
  • Catch up with HR.