AI Full-Stack Engineer

Make Your Mark

Cymulate’s Continuous Security Validation enables companies to challenge, assess and optimize their cyber-security posture against the evolving cyberthreat landscape, simply and continuously.

With world-class clients we strive to bring the highest level of service to everything we do. Our team is made up of the very best people for the job and as we grow, we’re always on the lookout for people with the skills, experience, and personality that will let us both shine. With high scores on Gartner, G2 and Glassdoor, our clients and employees have let us know what they love about us.

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What will you do

Design, build, and maintain production-grade AI-powered applications and services.

Develop end-to-end full-stack solutions, including backend services, APIs, and modern React-based frontends.

Build scalable, secure, and highly available distributed systems.

Develop AI agents, copilots, autonomous workflows, and intelligent automation.

Build and deploy RAG (Retrieval-Augmented Generation) solutions and integrate LLMs into production.

Design AI orchestration workflows using frameworks such as LangChain, LangGraph, or similar.

Implement AI evaluation, tracing, and observability pipelines using Langfuse or equivalent tools.

Develop MCP (Model Context Protocol) integrations and AI tooling ecosystems.

Build and maintain cloud infrastructure, CI/CD pipelines, and Infrastructure-as-Code.

Drive engineering productivity through AI-assisted development and automation.

Collaborate closely with Product, Design, and Engineering teams to deliver customer value.

Research and evaluate emerging AI technologies and introduce innovative solutions.

Own features end-to-end—from architecture and development to deployment, monitoring, and continuous improvement.

What will you have

5+ years of experience building scalable, production-grade full-stack applications.

Strong hands-on experience with TypeScript, Node.js, Python, React , and modern full-stack development.

Experience building AI-powered applications using LLMs (OpenAI, Anthropic, Gemini, etc.).

Hands-on experience with AI Agents, RAG, vector databases, prompt engineering, context engineering, and MCP .

Experience with AI frameworks such as LangChain, LangGraph, Langfuse, LlamaIndex , or similar.

Strong understanding of distributed systems, microservices, APIs, and cloud-native architectures.

Experience with AWS, Docker, Kubernetes, CI/CD , and DevOps best practices.

Ability to quickly learn and adopt emerging AI technologies and AI-assisted development tools.

Strong ownership mindset with the ability to independently deliver solutions from concept to production.

Experience building internal AI platforms or AI developer tools (advantage).

Familiarity with AI coding assistants such as Cursor, Claude Code, Windsurf, or GitHub Copilot (advantage).

Experience with multi-agent systems and autonomous workflows (advantage).

Background in SaaS or cybersecurity environments (advantage).

Experience leading technical initiatives or mentoring engineers (advantage).

Knowledge of AI security, model safety, and governance best practices (advantage).

Excellent communication skills, a collaborative mindset, and the ability to thrive in a fast-paced startup environment.

Passion for AI, curiosity, and a strong focus on innovation, execution, and business impact.