Must haves:

About The Role

We are seeking an AI-native Solution Architect with deep expertise in Node.js

ecosystems, Microservices Architecture, and No-Code/Low-Code platforms to

design scalable, resilient, and configurable SaaS solutions.

This role will be instrumental in building a generic, multi-tenant SaaS platform that

enables rapid product development while ensuring performance, security, and high

availability across a polyglot data infrastructure.

Key Responsibilities

• Define and drive architecture vision, standards, and governance practices.
• Architect and scale multi-tenant SaaS platforms using microservices and event-driven design.
• Design and standardize APIs, data architectures (SQL & NoSQL), and cloud-native/serverless systems.
• Establish strong DevOps, CI/CD pipelines, and reusable engineering patterns.
• Design and implement AI-native architectures using LLMs, embeddings, and vector databases.
• Establish AI patterns such as RAG, copilots, and workflow automation.
• Build prompt orchestration layers and AI gateway services.
• Define AI governance, security guardrails, and responsible AI practices.
• Drive AI-assisted engineering (code generation, documentation, automated reviews).
• Lead adoption of AI-powered development tools and LLM-driven workflows.
• Continuously evaluate and integrate emerging AI technologies.
• Collaborate cross-functionally and mentor engineering teams.
  
  

Experience & Skills

• 8+ years in software engineering, including 3+ years in solution architecture.
• Strong expertise in Node.js, microservices, event-driven systems, and REST/GraphQL APIs.
• Experience with SQL & NoSQL databases (PostgreSQL, MySQL, MongoDB, Elasticsearch).
• Hands-on experience with cloud platforms (AWS/GCP/Azure) and CI/CD & DevOps practices..
• Familiarity with No-Code/Low-Code platforms and workflow automation.
• Experience with LLM APIs, RAG architectures, and AI integrations in production systems.
  
  

Must Haves

• Active use of AI coding assistants (e.g., Claude, Cursor, Copilot) in daily development
• Strong prompt engineering skills for code generation, refactoring, and testing
• Experience working with agentic / multi-step AI workflows
• Understanding of AI limitations, risks, and hallucination handling
• Experience integrating LLMs into real-world applications (preferred)