We are looking for a highly accountable Full Stack Developer with 5+ years of experience, who is deeply skilled in building end-to-end applications and has strong hands-on expertise in AI/ML and Generative AI. This role requires more than just API integrationthe candidate should be capable in designing, developing, and deploying AI-driven systems.

The ideal candidate should thrive in startup environments, take ownership of outcomes, and independently drive development from concept to production.

Key Responsibilities :

- Design and build end-to-end full stack applications (frontend + backend + AI components).

- Develop, fine-tune, and deploy AI/ML and Generative AI models/solutions.

- Build intelligent features using LLMs, NLP, embeddings, vector databases, and agent-based architectures.

- Architect scalable backend systems using Python (FastAPI/Django/Flask).

- Develop modern, responsive frontends using TypeScript-based frameworks (React/Next.js/Angular).

- Take complete ownership of featuresfrom requirement understanding to production deployment.

- Optimize AI pipelines for performance, latency, and cost.

- Work closely with stakeholders in a fast-paced startup setup with high accountability.

Required Skills & Experience :

- 5+ years of experience in full stack development.

- Strong expertise in Python for backend and AI/ML development.

- Hands-on experience in AI/ML model development, not just integration.

Solid experience with Generative AI :

- LLMs (OpenAI, open-source models, etc.)

- Prompt engineering & evaluation

- RAG pipelines

- Vector databases (Pinecone, FAISS, Weaviate, etc.)

- Strong frontend development experience using TypeScript (React / Next.js preferred).

- Experience in designing and building scalable, production-grade applications.

- Strong understanding of databases (SQL/NoSQL).

- Experience with cloud platforms (AWS/Azure/GCP).

- Familiarity with Docker, CI/CD, and deployment pipelines.

Preferred Qualifications :

- Experience working in startup environments or high-ownership roles.

- Exposure to AI agents, autonomous workflows, or multi-agent systems.

- Experience with model fine-tuning or training pipelines.

- Understanding of MLOps practices.