Job Description
We are building the infrastructure for tomorrow. Apex Horizon Systems is seeking a visionary Lead AI Architect to define the technological roadmap for the year 2026. If you thrive at the intersection of cutting-edge Generative AI, Agentic workflows, and scalable distributed systems, this is your opportunity to shape the future of enterprise intelligence.
In this pivotal role, you will not just build models; you will architect the cognitive layer of our organization. You will lead a team of elite engineers in deploying next-generation Large Language Models (LLMs) and Autonomous Agents that will redefine how businesses interact with data.
Why join us?
- Work on proprietary, high-impact AI infrastructure.
- Competitive compensation package with equity options.
- Flexible remote-first culture with access to state-of-the-art compute resources.
- Opportunity to publish patents and set industry standards.
Ready to lead the AI revolution? Apply today.
Responsibilities
- Architect the 2026 Roadmap: Define and execute the technical strategy for deploying autonomous AI agents and generative AI models within the enterprise ecosystem.
- System Design: Design and implement high-throughput, low-latency inference pipelines using Kubernetes and GPU clusters.
- Model Optimization: Lead initiatives to fine-tune and distill large models for edge deployment, ensuring efficiency and cost-effectiveness.
- Team Leadership: Mentor senior engineers and data scientists, fostering a culture of innovation and technical excellence.
- R&D Collaboration: Partner with product teams to translate complex business requirements into robust AI technical solutions.
- Ethical AI Governance: Establish frameworks for fairness, transparency, and safety in AI decision-making processes.
Qualifications
- Education: MS or PhD in Computer Science, Machine Learning, or a related technical field.
- Experience: 8+ years of experience in software engineering, with at least 4 years dedicated to Machine Learning and Deep Learning.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and modern MLOps tools (MLflow, Kubeflow).
- Infrastructure: Strong understanding of distributed systems, cloud architecture (AWS/Azure/GCP), and containerization technologies.
- Leadership: Proven track record of leading high-performance engineering teams and delivering complex projects on time.
- Language: Fluent in English, with the ability to communicate complex technical concepts to non-technical stakeholders.