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Job Description (Posting).
Job Title: Enterprise Architect / Gen AI Software Engineer Architect
Job ID: 2776482
Position Type: Full-Time Employment
Location: Newark, New Jersey, USA
JD for Software Engineering Architect:
Experience: 10+ years in software engineering, with at least 3 years in architectural roles
Key Responsibilities:
- Lead the architecture, design, and development of enterprise-scale web applications with integrated Generative AI capabilities.
- Define technical standards, architectural patterns, and best practices for scalable and secure software systems.
- Collaborate with product, AI/ML, DevOps, and security teams to ensure alignment between business goals and technical execution.
- Oversee full-stack development lifecycle, ensuring robust design, performance tuning, and security compliance.
- Evaluate and integrate AI components such as LLMs, embedding services, and vector databases into product architecture.
Mandatory Technical Skills:
- Cloud-Native Architecture & Microservices
Proven experience designing scalable, cloud-native applications using microservices and event-driven patterns on Azure Ecosystem.
- Performance Optimization -
- GenAI Integration & LLM Orchestration
Hands-on with Generative AI technologies—Azure OpenAI, prompt engineering, RAG pipelines, embeddings, and vector search (e.g., Azure AI search, Azure PostgreSQL etc..). - Backend Engineering (APIs, Data, Security)
Strong expertise in REST APIs with versioning, throttling, and gateway integrations., PostgreSQL/MongoDB, OAuth2/SSO, and secure coding aligned with GDPR/SOC2 standards.
- Frontend Development (React/Next.js)
Deep experience building enterprise-grade UIs using React.JS, component libraries, and modern design systems.
- DevOps & Infrastructure as Code
Proficiency in Azure CI/CD pipelines , Docker, and Kubernetes for automated, scalable deployments.
- Real-Time & Scalable UI Patterns
Experience with WebSockets/SSE, UI performance optimization, and handling large-scale dynamic frontends.
- Testing, Observability & Quality Engineering
Competence in automated unit/E2E testing , frontend performance profiling, and monitoring of Deployed solutions.
- Gen AI
- AI-ML Modeling
- LLM
- Azure AI
- Azure Architecture