Job Description
We are seeking a visionary Senior Architect to lead our 2026 Vision Initiative. In a rapidly evolving technological landscape, the year 2026 represents a pivotal milestone for scalable, AI-driven infrastructure. As a key member of our elite technical team, you will be responsible for designing the backbone of our next-generation enterprise solutions, ensuring we are not just keeping pace with the future, but defining it.
You will bridge the gap between cutting-edge research and practical application, working alongside AI researchers and cloud engineers to deploy systems that are resilient, scalable, and future-proof.
Why Join Us?
- Impact: Architect the foundation for the next decade of computing.
- Flexibility: Hybrid work model with a focus on output and innovation.
- Growth: Direct mentorship from industry leaders in distributed systems.
Responsibilities
- Lead the architectural design for the 2026 roadmap, ensuring seamless integration of AI models with legacy infrastructure.
- Oversee the migration to serverless and edge computing architectures to support low-latency global applications.
- Establish security protocols and compliance standards (GDPR, SOC2) for all new infrastructure deployments.
- Conduct deep-dive code reviews and technical architecture reviews to ensure best practices and scalability.
- Collaborate with product managers to translate business requirements into robust technical blueprints.
- Drive the adoption of DevOps practices, automating CI/CD pipelines for maximum efficiency.
Qualifications
- 10+ years of experience in Systems Architecture, with a proven track record of leading large-scale infrastructure projects.
- Deep expertise in cloud platforms (AWS, Azure, or GCP) and containerization technologies (Kubernetes, Docker).
- Strong proficiency in programming languages such as Python, Go, or Rust.
- Experience designing distributed systems capable of handling high concurrency and data throughput.
- Excellent communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.
- Experience in implementing AI/ML model inference pipelines and MLOps workflows.