Principal Architect
Project description
Monitoring as a Platform, a platform that is the first critical step towards a self-managed infrastructure, and includes capabilities like real-time monitoring, intelligent networks, self-healing and IoT to achieve improved productivity, organizational agility and improved employee experiences.
Responsibilities
- * Develop and maintain architectural blueprints and high‑level system designs. * Define the overall architecture and set the technical direction for the organization. * Translate business requirements into feasible, scalable, and robust technical solutions. * Evaluate the client’s proposed technologies and assess their fit within the overall architecture. * Recommend appropriate tools, platforms, and architectural approaches. * Collaborate with engineering, product, and business teams to ensure the architecture meets functional and non-functional requirements. Provide architectural guidance and mentorship to engineering teams. * Ensure that systems meet enterprise standards for scalability, performance, reliability, and security. * Oversee monitoring, observability, and operational health of systems. * Architect systems leveraging AWS cloud services. * Integrate AI/ML infrastructure components and automation frameworks into the solution architecture. * Lead the design and optimization of ELK-based logging systems. * Guide the implementation of monitoring and visualization platforms such as Grafana. * Oversee infrastructure-as-code automation using Ansible and Terraform. * Support containerization and orchestration using Docker and Kubernetes.
SKILLS
Must have
- * 15+ years of experience in designing and documenting architectural blueprints. * 5+ years specifically in solution architecture or similar roles. * Knowledge and practical use of enterprise architecture frameworks. * Expertise in scalable system design and distributed systems. * Strong expertise in AWS cloud architecture and services. * Proficiency with Terraform and Ansible. * Advanced knowledge of monitoring and observability tooling. * Proficiency in the ELK stack (Elasticsearch, Logstash), including deployment and optimization. * Experience with Grafana for dashboards and visualization. * Experience with AI/ML infrastructure and automation frameworks. * Must-have! experience with the Traditional Machine Learning (Mathematics & Statistics, Core ML Algorithms, Learning Paradigms, Model Evaluation & Validation, Data Preparation, Deployment & MLOps, Tools & Frameworks: Python libraries, ML platforms: TensorFlow, PyTorch) Experiment tracking & reproducibility) * Hands-on experience with Docker and Kubernetes. * Excellent problem-solving skills. * Strong attention to detail. * Ability to collaborate across teams and communicate architectural decisions clearly.
Nice to have
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