Job Description
We are looking for a Lead AI Agent Architect to define the future of autonomous intelligence. As we approach the 2026 technological landscape, the industry is shifting from passive AI models to Agentic AI—systems capable of autonomous reasoning, planning, and execution.
In this pivotal role, you will lead the engineering of next-generation agent frameworks that integrate seamlessly with enterprise workflows. You will be responsible for the architecture of multi-agent systems that can self-correct, collaborate, and handle complex, multi-step tasks without human intervention.
What You Will Do:
Drive the technical vision for our autonomous AI ecosystem. You will work closely with researchers and product managers to build systems that are not just smart, but truly autonomous and reliable.
Responsibilities
- Architect and implement scalable multi-agent orchestration frameworks using Python and modern AI stacks.
- Design complex reasoning loops and memory mechanisms to enhance agent autonomy.
- Optimize LLM inference pipelines to reduce latency and operational costs.
- Establish best practices for AI safety, alignment, and ethical constraints in autonomous agents.
- Collaborate with cross-functional teams to integrate agents into legacy and modern software ecosystems.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field.
- 5+ years of experience in software engineering with a focus on Machine Learning or AI.
- Deep expertise in Large Language Models (LLMs), fine-tuning, and RAG (Retrieval-Augmented Generation).
- Strong proficiency in Python and frameworks such as LangChain, LangGraph, or AutoGen.
- Experience with distributed systems, cloud infrastructure (AWS/GCP), and containerization (Docker/K8s).