Agentic AI Engineer

⇒ Role Summary This role sits at the intersection of AI research, software engineering, and system design, with a strong focus on agent-based architectures and real-world deployment. Beyond core technical expertise, our client is seeking a candidate who is curious, experimental, and forwardthinking.

⇒ Main Responsibilities Design and implement agentic AI systems capable of planning, reasoning, and executing multi-step tasks. Develop and optimise AI agent workflows, including tool usage, memory management, and orchestration.

Comfortable with Remote Procedure Calls (RPC) such as gRPC for integrating with software ecosystem. Implement real-time decision engines and intelligent automation frameworks. Evaluate and improve agent performance through testing, benchmarking, and iteration.

Contribute to system architecture, ensuring robustness, scalability, and security. Stay current with the latest advancements in agentic AI, LLMs, and autonomous systems, and apply them where relevant. ⇒ Qualifications & Experience Bachelor's Degree in Information Technology or relevant fields.

At least 1–2 years of relevant work experience; fresh graduates are welcome. Strong programming expertise in Python. Proficiency in at least one of the following: C, C++, Golang, or Java. Hands-on experience with agentic AI frameworks and workflows (e. g. , LangChain, AutoGen, CrewAI, Semantic Kernel, or similar).

Solid understanding of LLMs and prompt engineering | Multi-agent systems and orchestration patterns | API integration and distributed systems. Experience building production-grade AI systems or microservices. Strong problem-solving skills and ability to work in complex, evolving environments.

Experience with real-time data processing or sensor-driven systems. Familiarity with decision engines, reinforcement learning, or planning algorithms. Knowledge of cloud platforms (Azure, AWS, or GCP) and containerized deployments such as docker. Experience working with vector databases, embeddings, and r