Job Description
We are Apex Future Systems, a pioneer in defining the technological landscape of 2026. We are building the world's most advanced autonomous agent ecosystems, moving beyond simple automation to true cognitive reasoning. We are seeking a visionary Lead Agentic AI Architect to lead our core engineering team in San Francisco.
In this pivotal role, you will not just write code; you will architect the future of human-machine interaction. You will design systems where AI agents possess the autonomy to plan, execute, and learn from complex, real-world environments. If you are passionate about pushing the boundaries of Generative AI and are excited about the roadmap for 2026, we want to hear from you.
Responsibilities
- Architect Agentic Workflows: Design and implement complex, multi-agent systems capable of autonomous decision-making and goal-oriented task execution.
- LLM Optimization: Lead the optimization of Large Language Models for inference speed and cost-efficiency at scale.
- Multi-Modal Integration: Integrate vision, audio, and text processing capabilities to create holistic AI agents.
- Research & Innovation: Stay ahead of the curve on emerging AI paradigms, specifically focusing on Reinforcement Learning from Human Feedback (RLHF) and Chain-of-Thought reasoning.
- Team Leadership: Mentor a high-performing engineering team, fostering a culture of innovation and technical excellence.
- Infrastructure: Build robust, scalable pipelines for training and deploying AI agents in production environments.
Qualifications
- Experience: 7+ years of experience in software engineering, with at least 3 years specifically in Artificial Intelligence and Machine Learning.
- Technical Skills: Deep expertise in Python, PyTorch, or TensorFlow; proven experience with Large Language Models (GPT-4, Llama, Claude) and Agentic frameworks (LangChain, AutoGPT).
- Education: Master’s or PhD in Computer Science, AI, or a related field.
- Architecture: Strong understanding of microservices architecture, distributed systems, and cloud infrastructure (AWS, GCP, or Azure).
- Problem Solving: Exceptional ability to translate abstract AI concepts into tangible, scalable product features.
- Communication: Excellent verbal and written communication skills, capable of presenting complex technical ideas to non-technical stakeholders.