Job Description
Are you ready to architect the technological landscape of 2026 and beyond? Apex Horizon Systems is seeking a visionary AI Infrastructure Architect to lead the next generation of intelligent enterprise solutions. We are not just building software for today; we are engineering the scalable, ethical, and robust systems required for the future.
In this pivotal role, you will define the architectural roadmap for our Generative AI and Machine Learning platforms. You will work closely with cross-functional teams to integrate cutting-edge LLMs, optimize inference pipelines, and ensure our infrastructure is resilient in a rapidly evolving digital ecosystem.
Why join Apex Horizon?
- Impact: Shape the core technology stack that will power industries for the next decade.
- Growth: Work in a high-growth environment focused on innovation and future-proofing.
- Compensation: Competitive salary plus comprehensive benefits and equity packages.
If you are a technical leader passionate about the intersection of AI, Cloud Architecture, and Future Tech, we want to hear from you.
Responsibilities
- Architectural Leadership: Design and implement scalable, distributed AI infrastructure capable of handling petabyte-scale data and complex model deployment.
- Roadmap Strategy: Define the technical roadmap for AI capabilities, specifically focusing on readiness for 2026 trends in autonomous systems and multimodal AI.
- Model Optimization: Lead initiatives to reduce model latency and cost, utilizing techniques such as quantization, pruning, and efficient serving architectures (vLLM, TensorRT).
- Collaboration: Partner with Data Science and Product teams to translate business requirements into robust technical architectures.
- Security & Compliance: Ensure all AI systems adhere to strict data privacy regulations and ethical AI guidelines.
- Technical Mentorship: Mentor junior engineers and architects, fostering a culture of technical excellence and continuous learning.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
- Experience: 5+ years of experience in software engineering, with at least 3 years specializing in Machine Learning Operations (MLOps) or AI Infrastructure.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, and distributed systems. Strong experience with containerization (Docker/Kubernetes) and cloud platforms (AWS, GCP, or Azure).
- AI Proficiency: Proven experience designing and deploying Large Language Models (LLMs) or Generative AI applications.
- Soft Skills: Exceptional problem-solving abilities and excellent communication skills to bridge the gap between technical teams and stakeholders.
- Future-Forward Mindset: Demonstrated interest in emerging technologies and the ability to anticipate industry shifts towards 2026.