Gen AI Fullstack Developer

Full Description

Gen AI Fullstack Developer

As a Gen AI Fullstack Developer, you will rapidly design, build, and iterate end to end AI-powered applications.

You will work across frontend, backend, and cloud infrastructure, integrating modern Gen AI technologies into production-ready systems.

You will collaborate closely with product, architecture, and engineering teams to deliver scalable, reliable, and high-impact solutions.

What you will do

In his role, you will:

• Build end to end fullstack applications using Python or TypeScript.

• Integrate Gen AI capabilities using LLM APIs and RAG architectures.

• Design and implement backend services using NestJS or Flask.

• Develop frontend experiences using React.

• Work with vector databases such as pgvector or similar technologies.

• Design and operate cloud infrastructure and CI/CD pipelines in Azure, AWS, or GCP.

• Implement monitoring, logging, and observability for production systems.

• Collaborate with PMs, architects, and engineers to define feasibility and delivery scope.

• Produce clear technical documentation and contribute to engineering best practices.

What you will bring

The top candidate will have the following skills:

• Bachelor's degree in CS, Engineering, or related, or equivalent practical experience.

• 5+ years of experience as a Fullstack Developer.

• Strong experience with Python or TypeScript.

• Strong experience building modern frontends with React.

• Strong experience building APIs and backend services with NestJS or Flask.

• Hands-on experience integrating LLM APIs and building RAG-based systems.

• Experience working with vector databases such as pgvector or similar.

• Solid DevOps experience, including Docker, CI/CD, and cloud platforms.

• Ability to prototype quickly and work effectively in ambiguous environments.

• Experience building and scaling production systems end to end.

Ideally you have…

• Experience working in startup or fast-paced product environments.

• Experience with open-source AI models.

• Experience with MLOps or AI observability tooling.

• Prior consulting or customer-facing delivery experience.

• Passion for applied AI, experimentation, and rapid iteration.

• Deep familiarity with at least one major cloud provider, Azure, AWS, or GCP.

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Confidentiality is assured, and only shortlisted candidates will be notified for interviews.