Job Description
Join Nexus Future Labs, a pioneer in next-generation cognitive computing, as we embark on Project 2026. We are not just building software; we are defining the architectural backbone of the human-machine interface for the decade ahead. If you possess the vision to turn theoretical AI capabilities into scalable, real-world infrastructure, we want to meet you.
As the Lead AI Architect, you will guide a world-class team of engineers, data scientists, and visionaries. You will be responsible for the end-to-end design of our proprietary neural grid, ensuring it is resilient, ethical, and ready to handle the exponential data growth predicted for 2026 and beyond.
Why Nexus Future Labs?
- Impact: Your work will directly influence the future of automation and decision-making.
- Autonomy: We trust our leaders to make strategic decisions with minimal red tape.
- Equity: Competitive stock options in a pre-IPO unicorn company.
Responsibilities
- Define and oversee the architectural strategy for Project 2026, ensuring alignment with long-term business goals and technological trends.
- Design scalable microservices architecture utilizing Kubernetes, Docker, and serverless technologies.
- Lead the integration of advanced Machine Learning models into production environments with zero downtime.
- Mentor senior engineers and foster a culture of technical excellence and innovation.
- Conduct rigorous code reviews and architectural audits to maintain system integrity and security.
- Collaborate with product and data science teams to translate complex research into robust engineering solutions.
- Stay ahead of the curve on emerging technologies (e.g., Quantum-ready architectures, edge computing).
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
- Experience: 10+ years of software engineering experience, with at least 5 years in a senior architectural or engineering leadership role.
- Technical Stack: Deep expertise in Python, Java, or Go; proficiency in cloud platforms (AWS, GCP, or Azure).
- AI/ML: Strong understanding of ML pipeline architecture, NLP, or Computer Vision frameworks (TensorFlow, PyTorch).
- Leadership: Proven track record of managing high-performing distributed teams across multiple time zones.
- Problem Solving: Demonstrated ability to solve complex, ambiguous problems with elegant, scalable solutions.
- Certifications: AWS Solutions Architect Professional or equivalent is highly preferred.