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:
o Tenant management
o Real-time voice runtime
o AI orchestration
o Telephony abstraction
o Compliance & audit layers
• Design and evolve multi-tenant SaaS architecture with:
o Tenant isolation (config, data, runtime)
o Shared core services
o Per-tenant policy enforcement
• Ensure platform supports configuration-driven agent creation, not code-heavy customization.
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B. Cloud & SaaS Engineering Leadership
• Lead cloud-native design on Azure, including:
o Kubernetes (AKS), microservices, event-driven systems
o API Gateway, WebSockets, WebRTC, NGINX
o Redis, Kafka/Event Hubs, Blob/Vector storage
• Define SaaS-grade non-functional requirements:
o Availability, scalability, latency, DR
o Tenant-level throttling and quotas
o Usage metering and billing hooks
• Drive cost-aware architecture decisions (compute, LLM usage, speech infra).
• Own environment strategy (dev / test / prod, tenant-scoped).
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C. Real-Time Voice & AI Orchestration
• Ensure ultra low latency
• Architect deterministic + AI hybrid flows:
o State machines / orchestration controlling AI calls
o Guardrails around compliance-critical steps
• Design failure-resilient voice flows:
o No mid-call drops
o Graceful degradation




o Fallback logic________________________________________
D. Delivery, Quality & Reliability
• Translate architecture into clear execution plans for GB06 leads.
• Review and approve:
o Architecture diagrams
o API contracts
o Data flows
o Runtime decisions
• Own production readiness:
o Observability, metrics, alerts
o Conversation replay
o Incident response patterns
• Ensure backward compatibility and controlled platform evolution.
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E. Compliance, Security & Governance
• Ensure platform meets financial services compliance:
o Consent, disclosures, call recording
o PII masking and access control
• Architect audit-first systems:
o Every call traceable
o Deterministic logs alongside AI outputs
• Drive Responsible AI practices:
o Explainability
o Bias checks
o Model/version governance
• Own fraud & spoofing architecture (voice biometrics, replay detection).
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F. People & Technical Leadership
• Lead and mentor across AI, Core Platform, Telephony, QA.
• Raise architectural maturity across teams.
• Own hiring and capability building for:
o Platform engineers
o AI 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
Bachelor’s or Master’s 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
• Solid system architecture & design skills (HLD/LLD).
• Deep experience with:
o Azure (AKS, networking, security, managed services)
o Microservices, event-driven architecture
o API gateways, WebSockets, WebRTC
• Working knowledge of:
o AI/ML & LLM-based systems (not research, but production usage)
o Speech pipelines (STT, TTS)
• Strong understanding of SaaS operational concerns:
o Billing, metering, quotas
o Observability and SRE principles
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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 (Maharashtra)
🏢 Bajaj Finance
📍 Maharashtra