Job Description
Are you ready to architect the future of autonomous intelligence? OmniVerse Tech is seeking a visionary Senior Agentic AI Engineer to join our elite San Francisco team. As we map out the technological roadmap for 2026, you will be at the forefront of building intelligent agents that reason, plan, and execute complex workflows autonomously.
In this pivotal role, you won't just be writing code; you will be defining the architecture that powers the next generation of enterprise AI. We are looking for a thought leader who combines deep technical expertise with a passion for the future of machine learning.
Why Join Us?
- Work on cutting-edge Agentic AI systems that solve real-world problems.
- Competitive compensation package with equity options.
- Flexible remote-first culture with a hub in the heart of San Francisco.
If you are passionate about shaping the AI landscape of tomorrow, we want to hear from you.
Responsibilities
- Design and deploy scalable, autonomous AI agent architectures capable of complex multi-step reasoning.
- Lead the research and implementation of Large Language Model (LLM) fine-tuning and Retrieval-Augmented Generation (RAG) pipelines.
- Optimize model inference performance and reduce latency in production environments.
- Collaborate with product managers to translate business requirements into technical specifications for 2026 roadmap items.
- Mentor junior engineers and contribute to a culture of technical excellence and innovation.
- Ensure the security, privacy, and ethical use of AI systems in compliance with industry standards.
Qualifications
- 5+ years of professional experience in software engineering, with at least 3 years specializing in Artificial Intelligence and Machine Learning.
- Strong proficiency in Python, PyTorch, or TensorFlow.
- Deep understanding of Natural Language Processing (NLP) and Large Language Models.
- Experience with vector databases (e.g., Pinecone, Milvus) and orchestration tools (e.g., LangChain, AutoGen).
- Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Bachelor’s degree in Computer Science, Engineering, or a related field (Master’s preferred).