Description
Purpose :
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
- Architectural Governance & Leadership :
- Define and drive the technical vision and architectural roadmap
- Establish engineering standards, design principles, and governance practices
- Lead architecture reviews, minimizing technical debt and ensuring scalability
- Maintain architecture documentation, system diagrams, and design standards
- Optimize CI/CD pipelines, DevOps practices, and PR automation workflows
- Platform Architecture & Design :
- Architect a multi-tenant SaaS platform using Node.js-based microservices
- Design scalable microservices and event-driven systems
- Define best practices for REST & GraphQL APIs
- Architect data strategies across :
- PostgreSQL
- MySQL
- MongoDB
- Elasticsearch
- Enable cloud-native and serverless architectures
- AI-Native Architecture & Integration :
- Design systems integrating:
- LLM APIs
- Embeddings & vector databases
- AI workflow orchestration
- Define patterns such as:
- RAG (Retrieval-Augmented Generation)
- AI copilots & automation workflows
- Prompt orchestration layers
- AI gateway services
- Establish AI governance, guardrails, and prompt security frameworks
- Engineering Excellence & Platform Enablement :
- Enable No-Code/Low-Code integrations for workflow automation
- Drive AI-assisted engineering practices, including:
- Code generation
- Automated documentation
- AI-driven code reviews
- Define reusable patterns for microservices, deployments, and automation
- Native AI Tooling Adoption :
- Promote usage of:
- Claude Code
- Cursor
- GitHub Copilot
- Build workflows leveraging LLMs for engineering productivity
- Evaluate and adopt emerging AI tools across the organization
- Cross-functional Collaboration
- Partner with Product, Engineering, DevOps, and Data teams
- Translate architecture into business-aligned outcomes
- Mentor engineers and contribute to capability building
Success Metrics
Commercial Impact :
- Faster time-to-market via No-Code/Low-Code enablement
- Reduced infrastructure costs through optimized architecture
Execution & Delivery
- Successful rollout of multi-tenant SaaS platform
- Adoption of AI-native workflows across engineering teams
Quality & Standards
- High system uptime, scalability, and security compliance
- Strong adherence to architecture and AI governance standards
Capability Building
- Improved team productivity via AI-assisted development
- Establishment of reusable microservices and deployment patterns
Experience & Skills
- 8+ years in software engineering, with 3+ years in Solution Architecture
- Strong expertise in :
- Node.js backend systems
- Microservices & event-driven architecture
- REST & GraphQL APIs
- Experience with databases:
- PostgreSQL, MySQL, MongoDB, Elasticsearch
Hands-on Experience With
- Cloud platforms (AWS / GCP / Azure)
- CI/CD & DevOps pipelines
- No-Code/Low-Code platforms
- Experience with:
- LLM APIs
- RAG architectures
- AI integrations in production systems
Native AI Capability (Mandatory)
- Daily usage of AI coding assistants (Claude, Cursor, Copilot)
- Strong prompt engineering skills for :
- Code generation
- Refactoring
- Test creation
- Ability to work in agentic / multi-step AI workflows
- Understanding of :
- AI limitations & hallucination risks
- Experience integrating LLM APIs into real systems (preferred)
Professional Qualifications
- Bachelors / Masters in Computer Science or related field
- Architecture certifications (preferred)
- Cloud certifications (e.g., AWS Solutions Architect) are a plus
(ref:hirist.tech)
