Design, develop, and integrate AI-powered applications and agentic workflows using modern LLM technologies.Build and maintain Model Context Protocol (MCP) servers, tools, resources, and integrations to enable AI agents to interact with enterprise systems.Develop orchestration frameworks and multi-agent workflows for coordinating AI agents, tools, APIs, and business processes.Integrate LLMs with REST APIs, databases, SaaS platforms, internal services, and external tools through secure and scalable architectures.Implement prompt engineering, tool/function calling, context management, memory, and RAG (Retrieval-Augmented Generation) solutions.Develop production-grade AI services with strong focus on scalability, reliability, observability, security, and performance.Work with engineering and product teams to translate business requirements into AI/agent-based solutions and technical architectures.Evaluate and optimize LLM models, agent performance, prompts, workflows, latency, and operational costs.Build automated testing, monitoring, logging, and evaluation frameworks to ensure quality and reliability of AI agents and MCP integrations.Stay current with emerging GenAI, MCP, agent orchestration, LLM, and AI engineering technologies, and contribute to best practices and technical standards.
