About The Role

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 .