Agentic AI Engineer

• Strong Python programming with hands-on AI/ML framework experience.
• Working knowledge of LLMs, prompt engineering, and basic fine-tuning (LoRA/QLoRA).
• Practical experience with agentic frameworks such as LangChain, AutoGen, or CrewAI.
• Experience with API integration and tool-augmented agent development.
• Understanding of responsible AI, safety guardrails, and LLM evaluation strategies.
• Familiarity with vector stores, retrieval systems, and RAG architectures
• Design and implement production-grade agentic architectures leveraging LLMs and reasoning engines.
• Build and optimise multi-agent systems for complex task orchestration and collaboration.
• Integrate external tools, APIs, and knowledge bases for robust agent augmentation.
• Tune agent performance for autonomy, adaptability, reliability, and safety.
• Embed agentic AI into enterprise workflows in collaboration with product teams.
• Prototype advanced capabilities: persistent memory, goal planning, and self-correction loops.
• Contribute to code reviews, technical documentation, and team best practices.
  
  

Good to Have

• Exposure to MLOps practices — experiment tracking, model versioning (MLflow, DVC).
• Knowledge of distributed systems and scalable backend architectures.
• Experience with cloud AI services on Azure, AWS, or GCP.