Job Description
We are seeking a visionary Agentic AI Lead to define the autonomous systems of tomorrow. As we prepare for the technological landscape of 2026, we are building the next generation of self-improving AI agents that can operate independently in complex environments.
In this role, you will bridge the gap between theoretical AI research and production-grade engineering, creating scalable architectures that prioritize autonomy, safety, and efficiency. You will lead a team of engineers and researchers dedicated to pushing the boundaries of what is possible with Large Language Models (LLMs) and multi-agent workflows.
Why Join Us?
Work on the cutting edge of AI evolution. We offer a competitive package, equity opportunities, and the chance to shape the future of intelligent automation.
Responsibilities
- Architect and implement scalable multi-agent systems using LLMs and reinforcement learning.
- Design robust guardrails and ethical frameworks to ensure AI agent safety and compliance.
- Optimize inference pipelines for low-latency, high-throughput autonomous decision-making.
- Collaborate with cross-functional teams to integrate AI agents into real-world enterprise applications.
- Research and prototype novel methodologies for agent memory, planning, and tool use.
- Mentor junior engineers and researchers in best practices for AI safety and prompt engineering.
Qualifications
- PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field.
- 5+ years of professional experience in software engineering, with 3+ years specifically in AI/ML.
- Deep expertise in Python, PyTorch, and modern LLM frameworks (LangChain, AutoGen, LlamaIndex).
- Strong understanding of vector databases and RAG (Retrieval-Augmented Generation) architectures.
- Experience deploying AI models to production environments using Kubernetes and cloud infrastructure.
- Proven track record of leading technical teams and driving complex projects from concept to deployment.