About our Client
Our client is a Private Equity-backed scaled SaaS solutions & services organization that caters to clients globally helping them maximise profitability through data and insights.
Roles & Responsibilties
- Own end-to-end architecture for AI/ML SaaS products (application, data, model, APIs) and define reference architectures and standards.
- Design scalable, multi-tenant, highly available global platforms with strong security, compliance, and observability.
- Drive AI/ML architecture and MLOps: model training/inference/deployment, feature stores, model registries, monitoring, and drift detection.
- Partner with Product and Data Science to translate business needs into scalable technical solutions and prioritize build vs. buy decisions.
- Lead and mentor a team of architects, run design reviews, maintain ADRs, and enforce technical guardrails to reduce technical debt.
- Influence long-term cloud and technology roadmap (AWS/Azure/GCP, GenAI/LLMs, vector DBs) and represent architecture in customer/stakeholder discussions.
- Ensure platform reliability and performance through SLOs/SLAs, observability, and operational best practices.
The Ideal Candidate
- 20+ years in software engineering/system architecture; 10+ years architecting enterprise Cloud/SaaS platforms
- Proven experience building and scaling AI/ML-driven products and production ML systems
- Hands-on with cloud-native architectures (AWS/Azure/GCP), Microservices, distributed systems, data-intensive apps
- Experience with MLOps, data pipelines, real-time processing and REST/GraphQL, Kafka & Kubernetes
- Prior senior architect roles (Principal, Chief Architect, Distinguished Engineer, etc.)
- Strong product mindset, excellent communicator, and proven leader/mentor
Good to have:
- Experience in multi-product/platform SaaS or late-stage startups
- Pre-sales or large enterprise deployment experience; open-source contributions or public speaking
On Offer
- Work on industry-leading enterprise SaaS products built out of India
- A culture that encourages experimentation, learning, and ownership
- Flat, collegial environment with fast growth opportunities
- Competitive compensation and generous health insurance
