Developer 

Job Description

Responsibilities:

1. Build and maintain full-stack applications, including frontend and backend systems powering AI features.
2. Integrate LLM APIs such as OpenAI and Google Gemini/Vertex SDK, as well as open-source models, into products.
3. Design and optimize end-to-end RAG pipelines including chunking, embedding generation, Qdrant indexing, hybrid retrieval, and reranking.
4. Build Graph RAG systems combining knowledge graphs such as Neo4j with vector search for multi-hop reasoning.
5. Develop prompt workflows and multi-step AI agents using LangGraph.
6. Train and fine-tune small language models (SLMs) for domain-specific tasks using LoRA, QLoRA, PEFT, and instruction tuning.
7. Prepare datasets and evaluate fine-tuning results.
8. Develop scalable REST/GraphQL APIs and data pipelines using Python and Node.js.
9. Design robust database schemas and data models for AI-driven features.
10. Create responsive and intuitive interfaces for AI-powered experiences using Next.js and React.
11. Deploy, monitor, and optimize services on AWS, GCP, or Azure.
12. Implement MLOps practices including model versioning, evaluation, CI/CD, and observability.
13. Build AI guardrails including input/output validation, prompt-injection defence, content filtering, PII redaction, and hallucination checks.
14. Apply security best practices across the stack, including secure APIs, secrets management, dependency scanning, and OWASP guidelines.
15. Own features end-to-end: scope with product, build, launch, measure, and iterate

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