Full Stack Engineer

Job Title

Full-Stack + Generative AI Engineer

Job Type

Full-time

About the Role

We are looking for a talented Full-Stack + Generative AI Engineer to build, deploy, and maintain AI-driven applications. You will work across frontend, backend, and AI / ML components to deliver features that leverage state-of-the-art generative models. You will collaborate with product, data science, and engineering teams to bring innovative solutions to production.

Key Responsibilities

Design, develop, and maintain full-stack web applications (frontend and backend) with clean, scalable, and maintainable code.

Integrate generative AI / large language models (LLMs) into user-facing applications (chatbots, intelligent assistants, content generation, etc.).

Build and maintain RESTful or GraphQL APIs for AI integration and data access.

Work on data pipelines, ingestion, and preprocessing of structured and unstructured data.

Use vector stores / embedding databases / semantic search (for RAG and other AI use cases).

Develop prompt engineering, fine-tuning, and model optimization for generative AI services.

Ensure system reliability, monitoring, and observability of AI services in production.

Collaborate with UX / design teams to build responsive and interactive frontends.

Ensure security, data privacy, and compliance in AI features.

Participate in code reviews, mentor junior engineers, and help define best practices.

Required Skills & Qualifications

Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).

At least 3–5 years of experience in full-stack development.

Strong proficiency in one or more backend languages / frameworks (e.g. Python - Flask, FastAPI, Django; Node.js; Java; etc.).

Good frontend skills using React / Angular / Vue (JavaScript / TypeScript).

Experience using cloud platforms (AWS, GCP, Azure) and working with containerization (Docker, Kubernetes).

Experience with AI / ML frameworks or services; familiarity with LLMs, prompt engineering.

Understanding of vector databases, embeddings, retrieval-augmented generation (RAG).

Solid understanding of REST APIs, microservices architecture.

Version control (Git), CI / CD pipelines, automated testing.

Preferred Skills

Prior work deploying generative AI solutions in production.

Experience with frameworks / libraries such as LangChain, LlamaIndex, etc.

Experience with agent-based architectures or multi-agent systems.

Skills in scaling and optimizing performance, latency, and resource usage.

Familiarity with real-time data / streaming, graph databases.

Experience in domain-specific AI (NLP, computer vision, or other relevant fields).