Cloud Architect.

Responsibilities Strategy and design: Develop cloud adoption plans and design the overall cloud architecture, including selecting appropriate cloud services from providers like AWS, Azure, or GCP. Implementation and migration: Oversee the migration of applications and systems to the cloud and ensure successful deployment. Management and optimization: Manage and monitor the cloud infrastructure for performance, cost, and security. This includes optimizing resource use and ensuring compliance with regulations. Collaboration: Work with stakeholders across various departments, including engineering, security, and executive leadership, to align cloud strategy with business needs. Technical guidance: Provide expert guidance to development teams on infrastructure and best practices. Continuous improvement: Stay updated on emerging cloud technologies and trends to identify opportunities for improvement and innovation. Ownership of end-to-end design, architectural and sustenance of entire Cognia systems Architect, design, and build core backend services for data ingestion, APIs, and real-time event processing across applications, infrastructure, and IAM domains. Designing, implementing, and managing an organization's cloud computing infrastructure to meet business goals. Key responsibilities include developing cloud adoption plans, overseeing cloud migrations, and ensuring the cloud environment is secure, scalable, and cost-effective. Architects also monitor and manage the cloud system, collaborate with other IT teams, and stay current with emerging cloud technologies to optimize performance. Define and maintain domain schemas (ECS-style) to normalize multi-source telemetry and enable correlation across app, infra, and identity data. Implement and optimize NoSQL and graph-based persistence layers using Firestore, MongoDB, and Neo4j. Build and secure multi-tenant APIs with robust authentication, RBAC, and contextual access control (OAuth2, JWT). Collaborate with AI/ML and frontend teams to expose explainable, composable APIs that power Cognia's reasoning and visualization layers. Design and oversee data contracts, event schemas, and message queues for inter-service communication. Lead architecture discussions, perform code and design reviews, and mentor engineers on backend best practices. Own DevOps integration for backend services - ensuring reliable deployment, observability, and scalability (AWS). Define and enforce engineering standards, including API versioning, error design, security policies, and testing frameworks. Define the architecture blueprint that supports the AI reasoning engine, telemetry ingestion, and explainable APIs Establish Cognia's core backend foundation Mentor leads & engineers and raise the technical bar across the team. Requirements 12+ years of backend engineering experience, with at least 3 years in architectural leadership roles. Deep expertise in microservice architecture, RESTful API design, and asynchronous/event-driven systems. Strong proficiency in Java Experience architecting and scaling data-intensive SaaS platforms using Firestore, MongoDB, and Neo4j (or equivalent). Proven experience building multi-tenant, secure systems with OAuth2, JWT, RBAC, and audit logging. Solid understanding of cloud-native architectures - containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines. Hands-on experience with AWS and infrastructure automation (Terraform, Cloud Build, GitHub Actions). Experience with Pub/Sub, Kafka, or other event-streaming systems for large-scale telemetry processing. Strong background in secure API development, data modeling, and runtime observability (logging, metrics, tracing). Excellent communication and mentoring skills - able to guide cross-functional teams and make sound architectural decisions with minimal oversight. Deep understanding of cloud platforms (e.g., AWS, Azure, GCP). Knowledge of cloud-native principles and technologies. Strong understanding of security principles and compliance requirements. Proficiency in areas like networking, databases, and servers. Excellent communication and collaboration skills Bonus Skills Experience with security data processing, AppSec, or DevSecOps tooling (e.g., Snyk, SonarQube, CodeQL). Familiarity with RAG/LLM-based pipelines or AI-driven services (collaboration with AI/ML teams). Exposure to GraphQL, gRPC, or OpenAPI-first design. Understanding of data lineage, provenance, or knowledge graph architectures.