Job Description
We are not just building software; we are architecting the reality of 2026. As the world accelerates towards Artificial General Intelligence and Quantum supremacy, Apex Horizon Technologies stands at the forefront. We need a visionary engineer to lead our Core Infrastructure team in defining the next generation of scalable, secure, and intelligent systems.
In this role, you will bridge the gap between theoretical AI potential and practical, deployable architecture. You will work with top-tier talent to solve complex problems that will define the tech landscape of the coming decade. If you are passionate about the future and have a knack for building systems that scale, we want to hear from you.
Why Join Us?
- Work on projects that shape the future of technology.
- Competitive equity and salary package.
- Flexible remote-first culture with a hub in SF.
Responsibilities
- Architect Future-Proof Systems: Design and implement scalable microservices and cloud-native architectures optimized for the high-performance demands of 2026.
- Lead AI Integration: Spearhead the integration of Generative AI models into core business workflows to enhance efficiency and user experience.
- System Optimization: Oversee the transition to next-gen data processing standards, ensuring zero-latency performance across distributed networks.
- Talent Mentorship: Guide a team of junior developers and data scientists, fostering a culture of continuous learning and innovation.
- Security & Compliance: Establish rigorous security protocols to protect proprietary data in an increasingly complex threat landscape.
- Technical Strategy: Collaborate with C-level executives to define long-term technical roadmaps and innovation strategies.
Qualifications
- Experience: 7+ years of experience in software engineering, with at least 3 years in a Senior Architect or Lead Engineer role.
- Technical Stack: Deep proficiency in Python, Rust, or Go, with extensive experience in cloud platforms like AWS, GCP, or Azure.
- AI Knowledge: Strong understanding of Machine Learning pipelines, neural networks, and large language models (LLMs).
- Problem Solving: Proven ability to architect solutions for complex, ambiguous problems.
- Communication: Exceptional verbal and written communication skills, capable of translating technical concepts to non-technical stakeholders.
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.