Full Stack Developer - Generative AI

Role Overview :

We are seeking a highly skilled Full Stack Developer with Generative AI expertise to design, develop, and deploy next-generation AI-powered applications. This role requires strong hands-on experience with LangChain, LangGraph, FastAPI, LLM integrations (OpenAI/AWS Bedrock), and modern frontend/backend development frameworks. You will play a key role in building scalable, production-ready Gen AI applications deployed on AWS cloud infrastructure.

Key Responsibilities :

Application Development & Architecture :

- Build responsive, interactive front-end applications using Angular, JavaScript, HTML, and CSS.

- Develop RESTful APIs and microservices in Python (FastAPI) and Java (Spring preferred).

- Architect and integrate Gen AI modules with enterprise applications.

Generative AI Integration :

- Apply prompt engineering and LLM fine-tuning strategies to deliver context-aware AI solutions.

- Enable semantic search, embeddings, and vector databases (Qdrant, MongoDB, PostgreSQL) for

intelligent applications.

Cloud & Deployment :

- Ensure smooth CI/CD pipelines, monitoring, and logging for production workloads.

- Optimize system performance, security, and cost-efficiency.

Collaboration & Leadership :

- Provide technical mentorship and contribute to code reviews, best practices, and system design discussions.

- Collaborate with cross-functional teams to integrate Gen AI capabilities into enterprise workflows.

Required Skills & Competencies :

- Backend Development: Python (FastAPI, LangChain, LangGraph), Java (Spring preferred).

- Frontend Development: Angular, JavaScript, HTML, CSS.

- Generative AI: Experience with LLMs (OpenAI, AWS Bedrock), prompt engineering, embeddings, and tuning.

- Cloud Expertise: Strong knowledge of AWS services (Lambda, API Gateway, S3, DynamoDB, EC2).

- Databases: PostgreSQL, MongoDB, Qdrant (vector DB).

- Strong understanding of RESTful API design, microservices architecture, and integration patterns.

Nice-to-Have Skills :

- Experience with Django/Flask for backend development.

- Understanding of AI/ML pipelines and model lifecycle management.

- Hands-on Java integration for embedding Gen AI modules into enterprise systems.

- Knowledge of DevOps practices (Docker, Kubernetes, Terraform, CI/CD pipelines).