Solution Architect - AI & MLOps Platforms

About the Role

• An AI-powered No-Code Platform for rapid web/app creation, and
• A robust Agentic AI/MLOps Orchestration Platform for enterprise-grade model management and automation.

You will own the end-to-end system architecturefrom conceptualization and high-level design to hands-on technical guidance and code reviews—ensuring that both platforms are scalable, modular, secure, and future-proof.

Key Responsibilities

2. Technical Oversight & Execution
 • Provide technical direction, code reviews, and mentorship to backend, frontend, DevOps, MLOps, AI/ML, and NLP teams—ensuring adherence to architecture and coding standards. • Oversee the implementation of AI/ML/NLP pipelines, ensuring modularity and smooth integration with product features (e.g., drag-and-drop builder, agent workflows). • Drive decisions around data management: model/data versioning, lineage, cataloging, storage, and secure data flows. • Ensure API gateway design, external integration readiness, and internal service discoverability. • Own the architectural roadmap for third-party integrations (e.g., Figma, Zapier, cloud vendors, payment gateways).

3. Performance, Scalability & Security
 • Define and enforce performance optimization strategies: API efficiency, database sharding/replication, horizontal scaling, caching layers. • Architect for high availability, disaster recovery, automated backups, and graceful failover. • Ensure SOC2/GDPR/ISO compliance readiness, robust audit logging, secrets management, and secure tokenization. • Oversee secure implementation of user management, authentication (OAuth2/SAML/MFA), and authorization. 

4. Cross-Platform Integration & Product Synergy
 • Design a shared foundation so that both platforms can leverage common services, data models, user management, and notification systems. • Architect for future extensibility: plugins, third-party module integration, and easy onboarding of new AI/ML workflows or UI blocks. • Partner closely with Product Management, UX/UI, and PhDs (AI/ML, NLP, HCI) to align technology with user and business needs. 

5. Delivery, Documentation & Continuous Improvement
 • Lead architecture sessions, whiteboarding, and design reviews with cross-functional teams. • Deliver comprehensive architecture documents, sequence diagrams, and decision logs. • Define technical KPIs: system uptime, API latency, model inference time, error rates. • Proactively identify architectural risks and bottlenecks—recommending refactors or redesigns as needed. • Champion a culture of innovation, security, quality, and continuous improvement. 

Required Experience & Skills

Desirable Skills

What Success Looks Like

Reporting & Collaboration

Why Join Us?