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 .