Job Description
We are building the intelligent infrastructure for the year 2026. We are seeking a visionary Senior Agentic AI Engineer to architect the next generation of autonomous agents. This role is for a builder who wants to move beyond simple chatbots and create systems that can reason, plan, and execute complex tasks autonomously.
About the Role
As a Senior Engineer, you will lead the technical strategy for our agentic AI products. You will work closely with researchers and product teams to design systems that leverage large language models (LLMs) to perform multi-step reasoning, interact with external tools, and operate safely in dynamic environments.
Key Responsibilities
- Design and implement robust autonomous agent architectures using modern frameworks (e.g., LangChain, AutoGen, CrewAI).
- Develop and optimize inference pipelines for LLMs to ensure low latency and high throughput.
- Implement memory management and context window strategies for long-running agent conversations.
- Conduct rigorous testing and evaluation of agent behaviors to ensure reliability and safety.
- Collaborate with cross-functional teams to define product requirements and technical roadmaps.
Qualifications
- Master’s or PhD in Computer Science, Machine Learning, or a related technical field.
- 5+ years of professional experience in software engineering, with at least 2 years in AI/ML.
- Deep understanding of LLMs, fine-tuning techniques, and prompt engineering.
- Proficiency in Python and frameworks such as PyTorch or TensorFlow.
- Experience with vector databases (e.g., Pinecone, Milvus, Weaviate) and RAG architectures.
Benefits
- Competitive salary and equity package.
- Comprehensive health, dental, and vision insurance.
- Flexible remote and hybrid work options.
- Professional development budget and access to cutting-edge AI tools.
Responsibilities
- Design and implement robust autonomous agent architectures using modern frameworks (e.g., LangChain, AutoGen, CrewAI).
- Develop and optimize inference pipelines for LLMs to ensure low latency and high throughput.
- Implement memory management and context window strategies for long-running agent conversations.
- Conduct rigorous testing and evaluation of agent behaviors to ensure reliability and safety.
- Collaborate with cross-functional teams to define product requirements and technical roadmaps.
Qualifications
- Master’s or PhD in Computer Science, Machine Learning, or a related technical field.
- 5+ years of professional experience in software engineering, with at least 2 years in AI/ML.
- Deep understanding of LLMs, fine-tuning techniques, and prompt engineering.
- Proficiency in Python and frameworks such as PyTorch or TensorFlow.
- Experience with vector databases (e.g., Pinecone, Milvus, Weaviate) and RAG architectures.