| Job Purpose | This role is responsible for translating business and product requirements into scalable cloud-native architectures ensuring real-time performance reliability compliance and cost efficiency while leading multiple AI and engineering teams building reusable PaaS capabilities rather than one-off solutions. |
| Duties and Responsibilities | A. Platform Architecture Ownership (Primary) Own the reference architecture for the Voice AI platform across: oTenant management oReal-time voice runtime oAI orchestration oTelephony abstraction oCompliance & audit layers Design and evolve multi-tenant SaaS architecture with: oTenant isolation (config data runtime) oShared core services oPer-tenant policy enforcement Ensure platform supports configuration-driven agent creation not code-heavy customization. B. Cloud & SaaS Engineering Leadership Lead cloud-native design on Azure including: oKubernetes (AKS) microservices event-driven systems oAPI Gateway WebSockets WebRTC NGINX oRedis Kafka/Event Hubs Blob/Vector storage Define SaaS-grade non-functional requirements: oAvailability scalability latency DR oTenant-level throttling and quotas oUsage metering and billing hooks Drive cost-aware architecture decisions (compute LLM usage speech infra). Own environment strategy (dev / test / prod tenant-scoped). C. Real-Time Voice & AI Orchestration Ensure ultra low latency Architect deterministic AI hybrid flows: oState machines / orchestration controlling AI calls oGuardrails around compliance-critical steps Design failure-resilient voice flows: oNo mid-call drops oGraceful degradation oFallback logic D. Delivery Quality & Reliability Translate architecture into clear execution plans for GB06 leads. Review and approve: oArchitecture diagrams oAPI contracts oData flows oRuntime decisions Own production readiness: oObservability metrics alerts oConversation replay oIncident response patterns Ensure backward compatibility and controlled platform evolution. E. Compliance Security & Governance Ensure platform meets financial services compliance: oConsent disclosures call recording oPII masking and access control Architect audit-first systems: oEvery call traceable oDeterministic logs alongside AI outputs Drive Responsible AI practices: oExplainability oBias checks oModel/version governance Own fraud & spoofing architecture (voice biometrics replay detection). F. People & Technical Leadership Lead and mentor across AI Core Platform Telephony QA. Raise architectural maturity across teams. Own hiring and capability building for: oPlatform engineers oAI engineers with production mindset Act as final technical escalation point. |
| Key Decisions / Dimensions | SaaS vs tenant-specific customization boundaries. Cloud architecture patterns and technology choices. Platform capability roadmap and deprecations. Model orchestration and runtime strategies. Cost vs performance trade-offs. |
| Major Challenges | Building a single platform that serves diverse enterprise use cases without fragmentation. Maintaining real-time guarantees while integrating LLM-heavy workflows. Scaling multi-tenant voice traffic with strict isolation and compliance. Balancing speed of innovation vs platform stability. Preventing architecture sprawl as teams grow. |
| Required Qualifications and Experience | Bachelors or Masters degree in Computer Science Engineering or related field. Experience 14 years in software / platform engineering. 5 years owning cloud-native SaaS or PaaS architectures. Proven experience building enterprise-scale multi-tenant platforms. Experience in real-time systems (voice video streaming) strongly preferred Technical Skills Strong system architecture & design skills (HLD/LLD). Deep experience with: oAzure (AKS networking security managed services) oMicroservices event-driven architecture oAPI gateways WebSockets WebRTC Working knowledge of: oAI/ML & LLM-based systems (not research but production usage) oSpeech pipelines (STT TTS) Strong understanding of SaaS operational concerns: oBilling metering quotas oObservability and SRE principles Leadership & Behavioural Skills Platform-first thinking (reuse > rebuild). Strong decision-making under ambiguity. Ability to align business product and engineering. High ownership and accountability mindset. |
National Lead Technology as a Business • Pune, Maharashtra, India
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