Senior AI Engineer

xperience 10+ years overall engineering experience, including 3+ years of hands-on experience building Generative AI/LLM-based solutions. Job Summary We are looking for an experienced Principal AI Architect / Staff Engineer to lead the design and development of our Generative AI and agentic AI capabilities. You will architect and build scalable, production-ready AI solutions using LLMs, AI agents, RAG pipelines, and cloud-native AI platforms. This is a highly hands-on technical leadership role where you'll own end-to-end AI architecture and mentor engineers while working closely with product, backend, and cloud teams. Key Responsibilities Design and architect end-to-end Generative AI and agentic AI solutions for production environments. Build AI agent workflows using LangChain, LangGraph, MCP , and integrate external tools and data sources. Design, implement, and optimize RAG (Retrieval-Augmented Generation) pipelines, embeddings, and vector databases. Define model selection strategies across multiple LLMs and SLMs , balancing quality, latency, cost, and security. Develop scalable AI services on AWS Bedrock, Google Vertex AI , or similar cloud AI platforms. Ensure production readiness through observability, monitoring, security, and reliability best practices. Collaborate with Product, Engineering, and Security teams to translate business problems into AI-powered solutions. Mentor engineers and drive technical excellence across the AI engineering team. Required Skills 10+ years of software engineering experience. 3+ years of hands-on experience building production-grade Generative AI applications. Strong experience designing AI architectures, not just integrating LLM APIs. Hands-on expertise with: Generative AI / LLMs LangChain / LangGraph MCP (Model Context Protocol) RAG architectures Vector databases (Pinecone, Weaviate, Milvus, Qdrant, pgvector, etc.) Embeddings and prompt engineering Experience with cloud platforms such as AWS (Bedrock) or Google Vertex AI . Strong knowledge of distributed systems, scalable backend architecture, and cloud security. Excellent problem-solving, communication, and technical leadership skills. Preferred Qualifications Experience contributing to or leveraging open-source AI frameworks. Experience building AI solutions for security, identity, or compliance-focused products. Familiarity with AI evaluation frameworks such as Ragas or similar tools. Prior experience in a product-based company or startup, owning systems end-to-end. What You'll Gain Opportunity to define the AI strategy for a cutting-edge product. Work alongside a senior engineering team on next-generation AI technologies. High ownership with end-to-end architectural decision-making. Exposure to the latest advancements in LLMs, AI agents, cloud AI platforms, and production-scale Generative AI systems.