AI Engineer

Company Overview:
Sundew is a leading digital transformation firm with an 18 year legacy of excellence. We are expertise in Digital Transformation, excelling in Digital Strategy, Cloud-Native Application Development, AI, and Product Engineering. As we expand, we are seeking an AI Engineer to join our AI team in designing, developing, and deploying next-generation autonomous and agentic systems for our global clients.

Roles and Responsibilities:

• Develop agentic AI systems capable of autonomous decision-making, task decomposition, and adaptive behavior in real-world or simulated environments.
• Design and implement cognitive architectures, memory systems, and planning algorithms to enable goal-driven, self-reflective agents.
• Integrate large language models (LLMs), symbolic reasoning, and other AI components into cohesive agent frameworks.
• Collaborate with cross-functional teams (e.g., product, UX, cloud engineering) to deploy agents in production environments.
• Optimize performance of agentic systems for scalability, latency, and robustness.
• Conduct experiments and evaluations on agent behavior, adaptability, and long-term autonomy.
• Stay current with research and best practices in autonomous agents, AI planning, reinforcement learning, and related domains.

Required Skills & Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Robotics, or a related field.
• Experience in AI/ML software development, with a focus on autonomous agents or AI planning.
• Strong proficiency in Python and familiarity with frameworks such as Lang Chain, Auto Gen, or custom agentic toolkits.
• Experience with LLMs, transformers, and integrating language models into agent workflows.
• Solid understanding of one or more of: reinforcement learning, cognitive architectures, symbolic reasoning, or decision-making systems.

Preferred Skills:

• Experience with cloud-based deployment of AI systems (e.g., AWS, GCP, Azure).
• Published work in agentic AI, multi-agent systems, or autonomous learning.
• Contributions to open-source agentic AI tools or frameworks.