Senior AI Engineer Agents

Requirements (Must-have):

• Experience: Minimum 5–7 years of overall software engineering experience with a proven track record of delivering production-grade systems.
• LLM & Prompt Engineering: Hands-on experience building with Large Language Models, including prompt and context engineering, tool/function calling, and retrieval patterns (RAG).
• Agent Frameworks: Practical experience with agentic frameworks, workflow orchestration tools, or automation platforms.
• Core Programming: Strong proficiency in Python and at least one additional backend language used in production services (e.g., C#, Java, Go, TypeScript).
• API Integration: Hands-on experience integrating with enterprise APIs and transactional systems, including rate limiting, error handling, and retry mechanisms.
• Software Engineering Practice: B.Sc. in Computer Science or related field, solid background in version control (Git), testing, CI/CD pipelines, code reviews, and production monitoring.

Nice-to-have:

• Experience in FinTech, banking, or high-volume transactional environments.
• Relevant technical certifications in cloud platforms (AWS, Azure, GCP), software engineering, or AI.
• Master's degree in Computer Science, Data Science, or a related field.

About the Project / Role Context:

For our client – an international FinTech & Telecom group – we are building a world-class AI capability (AI Squad) from the ground up. We create platforms, agents, and intelligent systems that will power the next generation of financial services across multiple markets.

We are looking for a Senior AI Engineer (Agents) to design and build production agents, workflows, and automations for day-to-day operations. This is a hands-on implementation role – you will write the code, integrate Model Context Protocol (MCP) servers and tools, test behavioral quality, and support the solutions in production.

,[Agent Development: Design and build production-ready AI agents and automations based on prioritized enterprise use cases., Tool & System Integration: Develop connectors, integrations, and Model Context Protocol (MCP) servers to connect agents with core enterprise APIs and transactional platforms., Testing & Behavioral Quality: Perform agent evaluation, behavioral testing, prompt tuning, and quality assurance for autonomous execution., Operational Support: Provide production support, monitoring, and incident response for deployed agents and workflow automations., Standards Alignment: Work closely with the Agentic & MCP Architect and Enterprise AI Architect to implement established safety guardrails, design patterns, and engineering standards.] Requirements: Python, Agentic AI, LLM, MCP (Model Context Protocol), RAG, API Integration, CI/CD