Gen AI Architect

Overview

Remote
$70+
Accepts corp to corp applications
Contract - W2
Contract - 12 Month(s)

Skills

Gen AI
Cloud Native
Azure
LLM

Job Details

Role: Software Engineering Architect Gen AI

Remote - Remote within EST time zone. will be required to work early from 6 am

Experience: 13+ years in software engineering, with at least 3+ years in architectural role

Key Responsibilities

  • Lead the architecture, design, and development of enterprise-scale web
  • applications with integrated Generative Al 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 Al components such as LLMs, embedding services, and
  • vector databases into product architecture.

    Mandatory Technical Skills

    1. Cloud-Native Architecture & Microservices

    Proven experience designing scalable, cloud-native applications using microservices and event-driven patterns on Azure Ecosystem.

    2. Performance Optimization

    Implementing caching strategies (Redis, CDN), asynchronous job processing

    3. Gen Al Integration & LLM Orchestration

    Hands-on with Generative Al technologies-Azure Open Al, prompt engineering, RAG pipelines, embeddings, and vector search (e.g., Azure Al search, Azure

    PostgreSQL etc..).

    4. 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.

    5. Frontend Development (React/Next.js)

    Deep experience building enterprise-grade Uls using React.JS, component libraries, and modern design systems.

    6. DevOps & Infrastructure as Code

    Proficiency in Azure CI/CD pipelines, Docker, and Kubernetes for automated, scalable deployments.

    7. Real-Time & Scalable UI Patterns

    Experience with WebSockets/SSE, Ul performance optimization, and handling large-scale dynamic frontends.

    8. Testing, Observability & Quality Engineering

    Competence in automated unit/E2E testing, frontend performance profiling.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.