Senior AI Engineer

As a Senior AI Engineer, you will play a crucial role in designing, developing, and deploying enterprise-grade Agentic AI solutions powered by LLMs. Your expertise in prompt engineering, agent orchestration frameworks, multi-agent architectures, memory and state management, RAG systems, and cloud platform deployment will be key to success in this role. Key Responsibilities: - Design and build LLM-powered agentic systems for planning, reasoning, tool usage, and multi-step workflow execution. - Develop orchestration pipelines using LangGraph, LangChain, or Semantic Kernel. - Implement agentic patterns such as Planner-Executor, ReAct, Supervisor-Worker, and Multi-Agent Collaboration. - Create and maintain reusable Agentic Skills, tool integrations, memory systems, checkpoints, and task-tracking mechanisms. - Lead prompt engineering efforts including system prompts, tool/function calling, structured outputs, guardrails, and instruction tuning. - Integrate APIs, enterprise services, search systems, and external tools into agent workflows. - Implement automated testing, evaluation frameworks, observability, tracing, monitoring, and cost optimization. - Ensure enterprise-grade security through prompt injection protection, RBAC, sandboxing, audit logging, and input/output validation. - Translate business requirements into technical designs, HLDs, LLDs, and scalable AI architectures. - Drive innovation by researching and implementing emerging Agentic AI techniques and best practices. Required Skills: - Strong hands-on experience with Prompt Engineering and Agentic AI development. - Expertise in LangGraph, LangChain, Semantic Kernel, or similar orchestration frameworks. - Experience with context engineering, memory management, state management, checkpoints, scratchpads, and task orchestration. - Proficiency in Python (preferred) or TypeScript/JavaScript. - Experience with RAG, hybrid retrieval, reranking, chunking, and vector databases (Pinecone, FAISS, Azure AI Search, etc.). - Knowledge of GitHub, DevOps, CI/CD, enterprise code management, and cloud platforms (Azure, AWS, or GCP). - Experience building user-facing AI applications such as chatbots, voice assistants, and workflow automation. - Strong analytical, problem-solving, communication, and stakeholder management skills. Preferred: - Experience with OpenAI Agent Skills, Claude Skills, or similar agent skill frameworks. - Experience with LLM evaluation frameworks, agent testing methodologies, and production-scale AI deployments. - Understanding of secure tool execution, cloud computing technologies, and modern AI trends. As a Senior AI Engineer, you will play a crucial role in designing, developing, and deploying enterprise-grade Agentic AI solutions powered by LLMs. Your expertise in prompt engineering, agent orchestration frameworks, multi-agent architectures, memory and state management, RAG systems, and cloud platform deployment will be key to success in this role. Key Responsibilities: - Design and build LLM-powered agentic systems for planning, reasoning, tool usage, and multi-step workflow execution. - Develop orchestration pipelines using LangGraph, LangChain, or Semantic Kernel. - Implement agentic patterns such as Planner-Executor, ReAct, Supervisor-Worker, and Multi-Agent Collaboration. - Create and maintain reusable Agentic Skills, tool integrations, memory systems, checkpoints, and task-tracking mechanisms. - Lead prompt engineering efforts including system prompts, tool/function calling, structured outputs, guardrails, and instruction tuning. - Integrate APIs, enterprise services, search systems, and external tools into agent workflows. - Implement automated testing, evaluation frameworks, observability, tracing, monitoring, and cost optimization. - Ensure enterprise-grade security through prompt injection protection, RBAC, sandboxing, audit logging, and input/output validation. - Translate business requirements into technical designs, HLDs, LLDs, and scalable AI architectures. - Drive innovation by researching and implementing emerging Agentic AI techniques and best practices. Required Skills: - Strong hands-on experience with Prompt Engineering and Agentic AI development. - Expertise in LangGraph, LangChain, Semantic Kernel, or similar orchestration frameworks. - Experience with context engineering, memory management, state management, checkpoints, scratchpads, and task orchestration. - Proficiency in Python (preferred) or TypeScript/JavaScript. - Experience with RAG, hybrid retrieval, reranking, chunking, and vector databases (Pinecone, FAISS, Azure AI Search, etc.). - Knowledge of GitHub, DevOps, CI/CD, enterprise code management, and cloud platforms (Azure, AWS, or GCP). - Experience building user-facing AI applications such as chatbots, voice assistants, and workflow automation. - Strong analytical, problem-solving, communication, and stakeholder management skills. Preferred: - Experience with OpenAI Agent Skill