Senior AI Engineer

- Design and architect modular AI agent frameworks incorporating skill decomposition, tool orchestration, and persistent state tracking.

- Build and deploy supervised and unsupervised ML models for prediction, classification, anomaly detection, and pattern recognition tasks in production environments.

- Develop decision-making loops that balance trade-offs between exploration vs. exploitation, cost vs. accuracy, and latency vs. reasoning depth.

- Build structured memory systems including episodic memory stores, semantic memory layers, and vector-based memory with optimised retrieval strategies.

- Design tool-calling architectures with strong execution validation, retry mechanisms, and failure recovery strategies.

- Develop evaluation frameworks to measure agent and model performance using task success metrics, rollout simulations, model accuracy benchmarks, and multi-sample validation approaches.

- Integrate AI agents and ML models with enterprise systems.

- Deliver production-ready AI systems that meet operational requirements around reliability, cost efficiency, throughput, observability, and enterprise security standards.