We are looking for a Senior/Lead AI Engineer to design, build, and scale end-to-end AI applications — including chatbots, agent workflows, and LLM-driven solutions. You will work directly with clients, drive technical decisions, and deliver production-grade AI systems that create real business impact. Responsibilities Design and deploy AI/LLM applications at scale (RAG, agentic systems, Q&A platforms) Architect solutions using agentic frameworks, integrating with vector databases and advanced memory architectures Build APIs, data pipelines, and enterprise integrations (CRM, ERP, cloud platforms) Evaluate and refine AI performance using LLM-based evaluation, agent metrics, and A/B testing Ensure performance, security, observability, and cost-efficiency across deployed solutions Conduct research, rapid prototyping, and experimentation to validate feasibility and business value Stay current with emerging AI protocols (MCP, A2A, ACP) and evolving LLM technologies Requirements 5+ years in AI/ML engineering with production-grade delivery experience Strong Proficiency in at least one modern programming language and web frameworks (Python, Java, Scala) Hands-on experience with major LLM platforms, agentic frameworks, and advanced integration patterns (RAG, agent orchestration, tool calling) Experience with vector databases, semantic/hybrid search, and retrieval/ranking systems Knowledge of MLOps/AIOps practices, monitoring, and security (including prompt injection prevention) Strong communication skills — able to translate complex AI concepts for both technical and non-technical audiences Ability to work independently, lead technical initiatives, and collaborate with cross-functional teams Technologies Languages: Python, Java, C#, Go Web Frameworks: FastAPI, Streamlit, Gradio, Flask, Spring Boot, ASP.NET LLM Platforms: OpenAI, Anthropic, Amazon Bedrock, Gemini Agentic Frameworks: LangChain, LangGraph, Semantic Kernel, LlamaIndex, Strands Agents Vector Databases: Qdrant, FAISS, Chroma, Pinecone, Weaviate Cloud AI Platforms: Azure OpenAI, Amazon Bedrock, GCP Vertex AI Enterprise AI: AWS AgentCore, Databricks AgentBricks, Google Agents Space, Azure AI Foundry On-Premise: vLLM Protocols: MCP, A2A, ACP MLOps/AIOps, observability, and security/guardrail tools for AI applications
