Senior AI Engineer (Agentic AI / AWS)
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 potential extension
COMMITMENT: Full-time
LOCATIONS: Europe-based, preferably CEE; remote, with potential future hybrid work in Prague
PROCESS: Initial qualification followed by technical and client interviews
NOTES: Fluent English is required. Strong AWS experience is highly preferred.
Responsibilities
- Architect and build production-grade autonomous AI agents and multi-agent orchestration frameworks.
- Develop reusable agent patterns and technical standards across multiple engineering squads.
- Integrate LLMs with APIs, databases, proprietary tools, and enterprise systems.
- Implement reliable tool-calling and structured-output workflows.
- Design and optimize prompt strategies, context management, memory, and agent state.
- Build stable, long-running agent workflows with appropriate error handling and recovery mechanisms.
- Implement monitoring, logging, tracing, and evaluation frameworks for agent behavior and model outputs.
- Support the deployment of AI systems on public cloud infrastructure, primarily AWS.
- Apply MLOps/AIOps practices across versioning, testing, monitoring, and evaluation.
- Collaborate 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 experience.
- Strong hands-on development experience with Python.
- Proven experience designing and integrating LLM-powered or agentic AI applications.
- Experience with agent orchestration frameworks such as LangChain, AutoGen, CrewAI, or comparable technologies.
- Strong experience with enterprise AI integration patterns including MCP, A2A, structured outputs, tool calling, or skills-based architectures.
- Professional experience designing and deploying AI solutions on public cloud platforms, preferably AWS.
- Experience with MLOps/AIOps practices, including versioning, testing, monitoring, and evaluations.
- Fluent professional English.