Job Title

About the RoleWe’re building the next generation of intelligent, autonomous AI systems and are seeking 2–3 experienced AI Engineers to join our product development team. You will play a key role in designing, building, and deploying AI agents and AI assistants that leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and scalable backend systems using PythonIf you love building things from scratch, experimenting fast, and scaling what works — this role is for you.Key Responsibilities- Design, develop, and deploy AI agents powered by cutting-edge LLMs (OpenAI, Anthropic, Mistral, Llama, etc.) - Building end-to-end retrieval-augmented generation (RAG) pipelines from ingestion, chunking, embeddings, and hybrid vector search, ideally using OpenSearch or other leading technologies. - Develop scalable Python microservices and APIs that support AI agent operations and LLM orchestration. - Own data ingestion and storage workflows — manage relational (PostgreSQL) and vector data for efficient retrieval and context management - Optimize agent reasoning and memory, improving accuracy, contextual continuity, and tool integrations - Collaborate cross-functionally with PMs, and designers to define and deliver AI-driven product features end-to-end - Implement monitoring, evaluation, and testing frameworks to measure model quality, latency, and reliability. - Stay ahead of the curve on emerging frameworks and new model capabilities.Required Skills- Bachelor’s or master’s degree in computer science, Artificial Intelligence, or related field. - Strong hands-on experience building and deploying LLM-powered applications - Proven experience with AI agents, AI assistants, or conversational systems - Solid understanding of Retrieval-Augmented Generation (RAG) architectures and search pipelines. - Strong proficiency in Python (FastAPI, Flask, or Django preferred) - Experience with vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus, pgvector, etc.) - Proficient in PostgreSQL and relational schema design - Familiar with AI agent and LLM orchestration frameworks (LangChain, LlamaIndex, Autogen, CrewAI, etc.) - Experience deploying AI systems to production (cloud, APIs, monitoring, scaling) - Familiar with Docker, Git, and CI/CD workflows - Proficiency in working with cloud platforms like AWS, Azure, or Google Cloud - Excellent problem-solving skills and analytical thinking. - Strong communication skills to collaborate with cross-functional teams. - Startup-oriented execution mindset, including: - Strong customer focus and ability to translate user needs into AI-driven solutions - High level of ownership across the full product lifecycle, from design to deployment - Ability to iterate quickly, experiment, and adapt in fast-moving environments - Bias for action with comfort making decisions under uncertainty.Nice to Have·Experience with agent frameworks (e.g., LangGraph, LangChain, AutoGen, CrewAI)·Familiarity with embedding models, re-ranking, and search relevance tuning·Experience building internal or customer-facing enterprise search or knowledge assistant products