Principal Backend Java Engineer – Platform (CE100SF RM 3771)

Position: Principal Backend Java Engineer – Platform (CE100SF RM 3771)

Responsibilities

Architect, design, and build core backend services for data ingestion, APIs, and real-time event processing across applications, infrastructure, and IAM domains.

Develop event-driven pipelines integrating data from GitHub, SAST tools, AWS Cloud, CI/CD logs, and security scanners.

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 customer’s core backend foundation

Mentor engineers and raise the technical bar across the team.

Requirements

8–10 years of backend engineering experience, with at least 3 years in microservices

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.

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.

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