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:
- Tenant management
- Real-time voice runtime
- AI orchestration
- Telephony abstraction
- Compliance audit layers

- Design and evolve multi-tenant SaaS architecture with:

- Tenant isolation (config, data, runtime)
- Shared core services
- Per-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:
- Kubernetes (AKS), microservices, event-driven systems
- API Gateway, WebSockets, WebRTC, NGINX
- Redis, Kafka/Event Hubs, Blob/Vector storage

- Define SaaS-grade non-functional requirements:

- Availability, scalability, latency, DR
- Tenant-level throttling and quotas
- Usage 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:
- State machines / orchestration controlling AI calls
- Guardrails around compliance-critical steps

- Design failure-resilient voice flows:

- No mid-call drops
- Graceful degradation




- Fallback logic

D. Delivery, Quality Reliability

- Translate architecture into explicit execution plans for GB06 leads.
- Review and approve:
- Architecture diagrams
- API contracts
- Data flows
- Runtime decisions

- Own production readiness:

- Observability, metrics, alerts
- Conversation replay
- Incident response patterns

- Ensure backward compatibility and controlled platform evolution.

E. Compliance, Security Governance

- Ensure platform meets financial services compliance:
- Consent, disclosures, call recording
- PII masking and access control

- Architect audit-first systems:

- Every call traceable
- Deterministic logs alongside AI outputs

- Drive Responsible AI practices:

- Explainability
- Bias checks
- Model/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:
- Platform engineers
- 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 Bachelors or Masters degree in Computer Science, Engineering, or related field.

- 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:
- Azure (AKS, networking, security, managed services)
- Microservices, event-driven architecture
- API gateways, WebSockets, WebRTC

- Working knowledge of:

- AI/ML LLM-based systems (not research, but production usage)
- Speech pipelines (STT, TTS)

- Strong understanding of SaaS operational concerns:

- Billing, metering, quotas
- Observability 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)
🏢 Bajaj Finance
📍 Pune