Full Stack Engineer

Job Title: Full-Stack Engineer (Python & Generative AI)Role OverviewWe are seeking a talented and driven 4 to 6 years of Full-Stack Engineer with deep expertise in Python and Generative AI to design, build, and deploy production-grade AI-powered applications.

In this role, you will bridge the gap between complex artificial intelligence models and intuitive, user-facing experiences.You will own the end-to-end development of advanced chatbot interfaces, conversational agents, and data retrieval systems leveraging Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs). The ideal candidate thrives at the intersection of robust backend infrastructure, slick user interfaces, and bleeding-edge AI orchestration.Key ResponsibilitiesAI Orchestration & Development: Design, implement, and maintain advanced RAG pipelines, including document ingestion, chunking strategies, semantic search, and vector database optimization.Backend Systems: Architect and build scalable, secure, and high-performance APIs and microservices using Python frameworks (e.g., FastAPI, Flask) to orchestrate LLM workflows and handle complex application logic.Frontend Engineering: Develop responsive, accessible, and intuitive UI components for chatbots, interactive dashboards, and AI copilots using modern frontend technologies (e.g., React, Next.js, or Vue.js).Agentic Frameworks: Implement agent-based architectures and multi-step conversational context management using orchestration tools like LangChain, LangGraph, or LlamaIndex.Performance & Reliability: Evaluate, version, and optimize prompt engineering templates to reduce hallucinations, cut system latency, and balance API runtime costs.Data & Infrastructure Management: Design schemas and optimize performance across relational databases (PostgreSQL/MySQL), NoSQL, and vector databases (e.g., Pinecone, Chroma, Milvus, Qdrant, PGVector).Required Skills & Qualifications1. Backend & AI LayerCore Language: Advanced proficiency in Python (async programming, multiprocessing, error handling, and object-oriented design).Frameworks: Hands-on experience with FastAPI, Flask, or Django.Generative AI & LLMs: Demonstrated experience integrating foundational models from major providers (OpenAI, Anthropic, Google, Azure) or hosting open-source variants (Llama, Mistral).RAG Expertise: In-depth knowledge of embeddings, hybrid search (BM25 + dense search), cross-encoders, reranking, and context window optimization.2. Frontend LayerLanguages & Tooling: Strong fundamentals in JavaScript/TypeScript, HTML5, and CSS3.Frameworks: Extensive experience with React.js, Next.js, or similar modern frameworks.State Management: Experience managing continuous state streaming (such as Server-Sent Events/WebSockets) for real-time chatbot response streaming.3. DevOps, Cloud & DatabasesDatabases: Comfort with both structured SQL and specialized vector stores.Cloud & Containers: Experience deploying AI applications on cloud providers (AWS, GCP, or Azure) using Docker containers.CI/CD: Proficient with Git and automated testing/deployment workflows.Nice-to-Have SkillsFamiliarity with LLM evaluation frameworks (e.g., Ragas, TruLens).Experience with fine-tuning open-source LLMs or parameter-efficient tuning techniques (LoRA/QLoRA).Familiarity with the Model Context Protocol (MCP) and tool-calling paradigms.Background in developing voice-enabled AI assistants or multimodal