Fullstack Developer (Node JS)

FULL-STACK AI ENGINEER (Node.js)

We're seeking a versatile Full-Stack AI Solutions Engineer. You'll be part of our AI Productization team, working across the entire technology stack to deliver custom AI solutions that make a real impact.

Youll grow expertise across multiple domains while contributing to research and AI implementation from concept to deployment.

As a Full-Stack AI Solutions Engineer, youll:

• Build full-stack applications:

  design and develop GenAI-based applications, RAG systems and agentic workflow automations.

• Research and integrate:

  looking for the most effective solutions to business problems, integrating existing products and frameworks, along with a wide range of our customers’ internal and external systems.

• Own the roadmap:

  shape the project from its concept to production deployment, ensuring high quality standards, impact and business value.

• Productionalize your solution:

  broaden your technology expertise by setting up infrastructure on major cloud providers, leveraging new managed services for AI/AIOps/MLOps, solving challenging setups (e.g. LLMs on-premise)

• Support AI adoption:

  be at heart of AI adoption among our customers, creating UI/UX prototypes of the brand-new solutions and products, proving the value and feasibility.

• University degree in Computer Science or related technical field

• 2+ years professional expertise with software engineering and Devops

• Proficiency in full-stack development in Node.js and React

• Hands-on experience with DevOps in cloud infrastructure (Azure, AWS), CI/CD pipelines

• Experience with database management (SQL and/or noSQL)

• A strong understanding of security best practices and performance optimization for scalable products
• Self-motivated with an ownership mindset to take initiative and deliver results in a fast-paced environment

Nice to have:

• Experience with AI tools, frameworks, and APIs (e.g., OpenAI, Hugging Face, LangChain).
• Experience with No-code/Low-code AI tools.
• Familiarity with integrating LLMs into practical use cases in real-world applications.
• Experience with Infrastructure as a Code solutions such as Terraform
• Certifications in cloud platforms like Azure of AWS.