Job Description
We are seeking a visionary Senior 2026 Readiness AI Architect to lead the strategic integration of next-generation artificial intelligence into our core infrastructure. As the tech landscape accelerates toward 2026, we need a thought leader to define the roadmap for scalable, ethical, and high-performance AI systems.
In this role, you will not only build models but also architect the future-proof ecosystems that will power our enterprise solutions. You will collaborate with cross-functional teams to translate complex business requirements into cutting-edge technical architectures, ensuring we are ahead of the curve for the year 2026 and beyond.
Why Join Nexus Horizon?
- Work at the forefront of the AI revolution.
- Competitive compensation package with equity options.
- Flexible remote-first culture with premium San Francisco amenities.
- Access to state-of-the-art computing resources and research labs.
Responsibilities
- Strategic Roadmap: Define and execute the technical vision for our 2026 AI Readiness Initiative, ensuring alignment with long-term business goals.
- System Architecture: Design scalable, fault-tolerant AI systems and microservices capable of handling high-throughput data streams.
- Model Development: Lead the research and deployment of Generative AI and Large Language Models (LLMs) tailored for enterprise applications.
- Team Leadership: Mentor a team of senior data scientists and ML engineers, fostering a culture of innovation and continuous learning.
- Performance Optimization: Drive initiatives to reduce model latency and improve inference accuracy in real-time environments.
- Ethical AI Governance: Implement guidelines and safeguards to ensure AI outputs are unbiased, transparent, and compliant with global regulations.
- Stakeholder Communication: Translate complex technical concepts for executive stakeholders and drive buy-in for new AI initiatives.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
- Experience: Minimum of 8+ years of experience in software engineering, with at least 5 years specifically focused on AI/ML architecture and deployment.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Deep understanding of distributed computing frameworks (Kubernetes, AWS SageMaker, GCP AI Platform).
- Strategic Mindset: Demonstrated ability to think several steps ahead regarding emerging trends in AI (e.g., Agentic AI, Multi-modal models).
- Leadership: Proven track record of leading high-performing engineering teams and managing cross-functional projects.
- Communication: Excellent verbal and written communication skills, with the ability to articulate complex technical strategies to non-technical audiences.
- Certifications: AWS Solutions Architect Professional, Google Professional Machine Learning Engineer, or equivalent is a plus.