AI / Solution Architect
Own end-to-end AI architecture for enterprise-grade platforms.
AI EngineeringBengaluru / Hybrid, India10+ years (incl. 5 in AI/ML architecture)Full-time
About this role
Own end-to-end AI architecture for enterprise-grade platforms, ensuring every component—from data layer to model serving—is scalable, secure, and measurable.
Own end-to-end AI architecture for enterprise-grade platforms.
Key Responsibilities
- Design modular AI reference architectures and integration patterns for mission-critical workloads
- Define interoperability standards, APIs, and data contracts across product lines
- Partner with product, data, and platform teams to embed AI safely inside existing estates
- Review solution designs for performance, observability, and cost efficiency
- Champion threat modeling, compliance, and Responsible AI principles
- Mentor architects and senior engineers on blueprints and implementation choices
Requirements & Qualifications
Required Qualifications
- 10+ years in solutions architecture with 5+ years building AI/ML systems
- Proven track record deploying ML systems at scale on AWS/Azure/GCP
- Depth in data modeling, feature stores, vector DBs, and API security
- Hands-on experience with MLOps stacks (Kubeflow, MLflow, Vertex, SageMaker)
- Excellent stakeholder management and technical storytelling skills
- Bachelor's/Master's in CS, Data Science, or related discipline
Preferred Qualifications
- Cloud certifications (AWS Solutions Architect Professional, Azure Architect Expert)
- Experience with multi-cloud and hybrid cloud architectures
- Published research in AI/ML conferences or journals
Required Skills & Technologies
AI ArchitectureMLOpsAWS/Azure/GCPFeature StoresVector DatabasesAPI DesignKubeflowMLflow
Benefits & Perks
Competitive salary and performance bonuses
Flexible hybrid work arrangement
Health insurance for you and your family
Learning and development budget