Senior AI Engineer (Agentic AI / AWS) - REMOTE

About Gramian Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About The Role Our client is a Big4 Consultancy group that works with leading financial institutions on AI-driven transformation, automation, advanced analytics, and financial crime prevention. Their work spans intelligent fraud detection, AML/KYC modernization, autonomous workflows, enterprise AI platforms, and the secure industrialization of AI in highly regulated environments. We are looking for Senior AI Engineers to design, build, and deploy production-grade autonomous agents, multi-agent systems, and LLM-powered enterprise applications. The role will work across multiple delivery squads and focus on reusable architecture, agent orchestration, tool integration, cloud deployment, and evaluation of long-running AI workflows. CONTRACT: Contractor assignment, expected October 2026 - July 2027, with extension available (and retainer rate) COMMITMENT: Full-time LOCATIONS: REMOTE 100%, Europe-based and EU authorization PROCESS: Initial qualification followed by technical and client interviews NOTES: Fluent English is required. Must have authorization for EU work. Responsibilities Architect and build production-grade autonomous AI agents and multi-agent orchestration frameworksDevelop reusable agent patterns and technical standards across multiple engineering squadsIntegrate LLMs with APIs, databases, proprietary tools, and enterprise systemsImplement reliable tool-calling and structured-output workflowsDesign and optimize prompt strategies, context management, memory, and agent stateBuild stable, long-running agent workflows with appropriate error handling and recovery mechanismsImplement monitoring, logging, tracing, and evaluation frameworks for agent behavior and model outputsSupport the deployment of AI systems on public cloud infrastructure, primarily AWSApply MLOps/AIOps practices across versioning, testing, monitoring, and evaluationCollaborate with engineering, data, cloud, and business teams to deliver secure and scalable AI solutions Requirements 5-10 years of professional software, data, or AI engineering experienceStrong hands-on development experience with PythonProven experience designing and integrating LLM-powered or agentic AI applicationsExperience with agent orchestration frameworks such as LangChain, AutoGen, CrewAI, or comparable technologiesStrong experience with enterprise AI integration patterns including MCP, A2A, structured outputs, tool calling, or skills-based architecturesProfessional experience designing and deploying AI solutions on public cloud platforms, preferably AWSExperience with MLOps/AIOps practices, including versioning, testing, monitoring, and evaluationsFluent professional English