Architecture & Design Leadership
- Define and lead the overall solution architecture, component boundaries, APIs, data flows, and cloud / service integrations.
- Architect microservices-based, API-first backends for both platforms.
- Design for multi-tenancy, RBAC, internationalization, and privacy-by-design.
- Implement collaboration frameworks (e.g., CRDT / OT), version control, and rollback systems.
- Lead architecture for LLM / AI agent integration : inference pipelines, caching, prompt orchestration.
- Set technical standards for cloud infrastructure, containerization (Docker, K8s), and ML ops tools (MLflow, Airflow, etc.).
Technical Oversight & Execution
Provide mentorship and code / architecture reviews across backend, frontend, DevOps, and AI teams.Oversee integration of AI / ML pipelines into product features.Drive decisions on data lifecycle : versioning, lineage, cataloging, and secure flows.Ensure effective API gateway design and service discoverability.Define the roadmap for third-party integrations (Zapier, Figma, payments, cloud).Performance, Scalability & Security
Architect for scale : sharding, caching, horizontal scaling, and efficient API performance.Ensure high availability, disaster recovery, and graceful failover mechanisms.Implement compliance frameworks (SOC2, GDPR, ISO), secure tokenization, audit logging.Oversee authentication / authorization : OAuth2, SAML, MFA, RBAC.Cross-Platform Integration & Product Synergy
Create a shared foundation across platforms—user management, services, and data models.Enable plugin architecture and future extensibility.Collaborate with Product, UX, and research teams (AI / ML, NLP, HCI) to align tech with product goals.Delivery, Documentation & Continuous Improvement
Run whiteboarding sessions, design reviews, and architecture alignment meetings.Maintain architecture documents, diagrams, and decision logs.Track system KPIs : uptime, latency, inference time, error rates.Proactively identify and resolve architectural risks or tech debt.Foster a culture of innovation, quality, security, and agility.Requirements & Skills
10+ years of software engineering experience, with 4+ years in complex cloud-native architecture.Proven success designing microservices / SOA for scalable AI / ML platforms.Strong knowledge of no-code builders or MLOps systems.Hands-on with :Cloud : AWS, GCP, AzureContainers & Orchestration : Docker, KubernetesML Pipelines : MLFlow, Airflow, KubeflowSecurity : OAuth2, SAML, RBAC, GDPR complianceCI / CD, Monitoring, LoggingExperience integrating LLMs, prompt management, and agent orchestration.Built systems handling millions of users and / or enterprise-scale workloads.Excellent communication, documentation, and leadership skills.Desirable Skills
Integration experience with tools like Figma, ZapierFamiliarity with blockchain-based data security or token systemsPrior experience in AI-powered drag-and-drop builders or agentic SaaS toolsExperience in distributed, fast-paced startup environmentsSuccess Metrics
Robust MVP launch with minimal tech debtHigh system availability, extensibility, and reliabilitySmooth AI / ML feature integration with low-latency inferenceRapid onboarding of developers and users with scalable architectureSkills Required
Cloud Architecture, Microservices, MLops, Kubernetes, Docker