Strong programming skills in Python and experience with AI/ML frameworks.
- Deep understanding of LLMs, prompt engineering, and fine-tuning techniques.
- Familiarity with agentic frameworks (LangChain, AutoGen, CrewAI, or similar).
- Knowledge of reinforcement learning, reasoning algorithms, and planning systems.
- Experience with API integration and tool augmentation for agents.
- Strong grasp of ethical AI principles and safety mechanisms. Responsibilities:
- Design and implement agentic architectures leveraging LLMs and reasoning engines.
- Develop multi-agent systems for task orchestration and collaboration.
- Integrate external tools, APIs, and knowledge bases for agent augmentation.
- Optimize agent performance for autonomy, adaptability, and safety.
- Collaborate with product teams to embed agentic AI into business applications.
- Research and prototype advanced capabilities like memory, planning, and self-improvement Experience:
- 6–10 years of experience in AI/ML engineering, with at least 2+ years in building agentic AI systems or LLM-based applications. Preferred Qualifications:
- Hands-on experience with GenAI-powered solutions and multi-modal models.
- Background in distributed systems and scalable architectures.
- Ability to work in fast-paced, research-driven environments
