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 retrieval systems.

⇒ Research & Innovation Expectations

• Actively keeps up with recent research trends in Agentic AI, LLM orchestration, and autonomous systems.
• Evaluates and prototypes emerging techniques from academic and industry research.
• Brings forward new ideas and improvements to enhance system capabilities.

⇒ Key Attributes

• Strong ownership mindset and ability to deliver end-to-end solutions.
• Curiosity-driven with a passion for emerging AI technologies.
• Ability to balance research insights with practical implementation.
• Effective communicator with a collaborative approach.