Job Purpose
Bajaj Finserv Web is a critical component of the company's omnipresence strategy. You will be working with India's largest NBFC's web technology stack, encompassing over 40 business lines and 230+ features, with nearly 500 million traffic and managing over 30,000 webpages.
It is an integrated platform offering a portfolio of products covering payments, cards, wallets, loans, deposits, mutual funds, and loans on lifestyle products, ranging from consumer durables to home furnishings.
The Principal Architect is the design authority for this entire customer-facing digital estate and leads a group of 4-5 Technical Architects spanning AEM and content platforms, frontend frameworks, cloud and platform engineering, and AI and data. The role is deliberately multi-stack: it is accountable for a single coherent North-star architecture across content, experience, services, cloud and intelligence layers, rather than for the depth of any one stack. Deep, demonstrable AI engineering capability is a mandatory requirement of the role - the Principal Architect defines how LLM, agentic and evaluation-driven systems are architected, governed and run inside a regulated NBFC. Above all, the role exists to change the status quo: to identify where the current architecture, engineering practice or cost base is structurally limiting, and to sponsor and land the initiatives that move it, with measurable outcomes on performance, velocity, resilience and total cost of ownership.
Duties and Responsibilities
• Ensure architecture, decision records and runbooks are documented, current and usable, so that platform knowledge does not sit only with individuals.
5. Leadership and Team Development
• Lead, coach and grow 2-4 Technical Architects - set objectives, conduct reviews, close appraisal cycles on time, and build a genuine succession bench for each stack.
• Deliberately build cross-stack breadth in the architect group so that the organisation is not exposed to single-person dependency in any technology area.
• Own senior technical hiring - define the bar for GB06 and GB05 bands, chair architecture-level interview panels, and hold the line on technical depth including the mandatory AI engineering bar.
• Determine individual training and development plans, sponsor certification and conference participation, and create visible technical career paths for engineers below the architect band.
• Inspire and influence across the organisation - present technology strategy, priorities, quarterly plans and investment cases to Vertical Head, CIO and MD level forums and secure buy-in.
• Ensure high engagement and morale across the engineering group through sound management intervention and a high degree of emotional intelligence.
• Keep delivery activity firmly connected to business outcomes, working with cross-functional teams on acquisition, conversion and cross-sell targets.
6. Risk, Compliance and Commercial Governance
• Own the architecture-level risk posture for the estate covering information security, data privacy and localisation, third-party and supply chain risk, and regulatory obligations applicable to an RBI-regulated NBFC.
• Partner with Information Security, Risk, Compliance and Internal Audit as the technical counterpart on reviews, findings and remediation, and represent the platform architecture in regulatory and audit engagements.
• Own cloud and platform cost architecture - FinOps discipline, unit economics, commitment and reservation strategy, egress and inference cost control - and hold the group accountable to the cost envelope.
• Lead technical evaluation for vendor selection, RFPs and renewals, define exit and portability requirements in contracts, and support commercial negotiation with technical leverage.|1. Enterprise Technology Architecture and North-star Roadmap
• Own the North-star architecture for the customer-facing digital estate end to end - content and DXP, experience and rendering, API and integration, cloud and runtime, data and intelligence - and ensure the individual stack architectures resolve into one coherent target state rather than four adjacent ones.
• Define, publish and govern reference architectures, architecture principles and non-functional standards covering security, performance, scalability, availability, observability and cost, and make them binding across all PODs and partner vendors.
• Own the multi-year technology roadmap and sequencing across concurrent modernisation programmes, ensuring each stack's roadmap accounts for new and yet-to-release capabilities of the underlying products and frameworks.
• Maintain a technology radar with explicit adopt, trial, hold and retire positions, and drive deliberate retirement of technologies and patterns that have outlived their fit.




• Own build versus buy versus partner decisions with a defensible commercial case - TCO, exit cost, lock-in exposure, capability fit and time to value - and present the recommendation to CIO and MD level forums for sign-off.
• Own the architecture of platform resilience - auto-scale, graceful degradation, failure domain isolation, multi-CDN and multi-region strategy, disaster recovery and peak season readiness across the full estate.
• Set the integration and contract strategy across content platforms, commerce, core lending and servicing systems, and internal data platforms, covering API, event-driven and BFF patterns.
• Create and run a validation framework that measures and reports the effectiveness of the architecture across performance, reuse, defect density, delivery velocity, availability and cost per unit of traffic.
2. AI Engineering and Applied Intelligence (mandatory core of the role)
• Own the architecture for LLM and agentic systems across the estate - model selection and routing, retrieval and context architecture, orchestration and workflow durability, tool and function design, memory and state handling, and cost and latency engineering at production scale.
• Define the evaluation discipline for all AI systems: deterministic gates, LLM-as-judge scoring, golden datasets, regression harnesses, drift detection and human-in-the-loop review, so that AI capability is released against evidence rather than demonstration.
• Own AI guardrail and governance architecture - prompt injection and jailbreak defence, output safety and hallucination controls, PII handling, content provenance and watermarking, model and prompt versioning, and full auditability of AI-influenced decisions.|• Ensure every AI workload meets regulatory obligations applicable to a regulated NBFC, including data localisation and in-region inference, written vendor confirmation of data egress and retention behaviour, and alignment with emerging AI assurance standards such as ISO 42001.
• Drive AI into the software delivery lifecycle itself - agentic coding harnesses, automated review and test generation, design-to-code pipelines and documentation automation - with instrumented, measured impact on engineering throughput and defect rates rather than anecdotal adoption claims.
• Set the standard for what qualifies as production-grade AI engineering across the group, and personally review the architecture of every significant AI initiative before it is funded or scaled.
3. Engineering Initiatives, Innovation and Status Quo Disruption
• Identify, structure and sponsor the engineering initiatives that materially shift the platform - replatforming, decomposition, rendering and edge strategy changes, developer experience overhauls, observability and quality step-changes - and carry them from hypothesis to landed outcome.
• Challenge incumbent architecture, tooling and vendor arrangements on evidence, and be willing to retire established solutions where the data supports it.
• Run a disciplined POC and benchmarking practice with pre-agreed success criteria, cost envelopes and kill conditions, so that experiments conclude rather than accumulate.
• Own engineering productivity as a measurable outcome - cycle time, change failure rate, lead time to production, environment and pipeline efficiency - and drive the initiatives that improve it across all PODs.
• Establish industry benchmarking and competition mapping as a standing input to technology decisions, and scout the landscape - including the external start-up ecosystem and internal incubators - for capabilities worth introducing.
• Foster a culture of engineering excellence across the enterprise: modern engineering practice, open source and open standards adoption, responsible use of AI-assisted development, internal technical forums, and published engineering writing.
4. Architecture Governance and Delivery Assurance
• Chair the architecture review and design authority forum, approving solution designs, granting or refusing architecture exceptions, and maintaining the exception register with agreed remediation timelines.
• Assure delivery quality across PODs through architecture-level quality gates - performance budgets, security review, accessibility, SEO and GEO, observability readiness and release criteria.
• Own the enterprise technical debt position: maintain a prioritised register, quantify the business cost of carrying it,



and secure funded remediation as part of the annual plan rather than as spare capacity.
• Act as the final technical escalation point for cross-stack production incidents, lead architecture-level root cause analysis, and drive systemic preventive action.
Key Decisions / Dimensions
Following decisions are taken by the role:
• Target-state architecture, architecture principles and binding non-functional standards for the entire customer-facing estate.
• Technology radar positions - what is adopted, trialled, held and retired across all stacks.
• Build versus buy versus partner decisions, and the technical recommendation on vendor selection, renewal and exit.
• AI architecture decisions - model and platform selection, inference region and residency posture, orchestration approach, evaluation and guardrail standards, and which AI initiatives are funded or stopped.
• Approval or refusal of architecture exceptions raised by Technical Architects, and the remediation terms attached to any exception granted.
• Cloud, CDN, edge and multi-region strategy, including failover, disaster recovery and peak season readiness posture.
• Prioritisation and funding case for technical debt remediation and platform engineering investment.
• Sequencing and phasing of modernisation and migration programmes across PODs.
• Technical hiring bar for architect and SDM bands, and the structure and allocation of the architect group across stacks.
• Which engineering initiatives are sponsored, and the success criteria and kill conditions applied to every POC.
• Final technical call on cross-stack production escalations and on release go / no-go where architecture risk is material.
Major Challenges
• Holding one coherent target architecture across four to five distinct technology stacks, each with its own vendor roadmap, release cadence and specialist community.
• Landing large modernisation programmes on a live, high-traffic, revenue-bearing estate without regression on organic traffic, analytics, conversion or regulated journeys.
• Adopting quick-moving AI capability at production scale while satisfying data localisation, auditability and model risk expectations in a regulated NBFC - where the regulatory position is still maturing faster than the technology guidance.
• Driving architectural consistency across 15-20 PODs and multiple partner vendors when delivery pressure consistently rewards local shortcuts.
• Balancing innovation and structural change against run stability, peak season readiness and an unrelenting business change backlog.
• Building and retaining genuine depth - particularly AI engineering depth - in a market where that capability is scarce and highly mobile.
• Making irreversible, high-cost technology decisions under incomplete information and compressed timelines.
Required Qualifications and Experience
a) Qualifications
B. Tech / B.E. - Computer Science or equivalent Engineering discipline
Post-graduation preferably from a Tier 1 college is an added advantage
Certifications preferred: AWS Certified Solutions Architect - Professional, Adobe Certified Master - AEM Architect, TOGAF or equivalent architecture certification

b) Work Experience
• Core Requirement: 14-18 years in software engineering with a minimum of 5 years in a formal architecture role, including proven accountability for a large-scale, high-traffic customer-facing estate, preferably in BFSI, Fintech or Ecommerce.
• Leadership Scale: Must have led architects and engineering managers directly, with indirect responsibility for 100+ engineers across multiple PODs, locations and partner vendors.
• Multi-Stack Breadth (essential): Credible hands-on depth in at least two, and working architectural command of all, of the following: content and DXP platforms (AEM 6.5+ / AEMaaCS, headless CMS such as Sanity or Contentful), modern frontend (Next.js, React, TypeScript, design systems, Core Web Vitals), backend and services (Java / JEE, Node JS, REST, GraphQL, event-driven and BFF patterns), and cloud and platform engineering.
• Cloud and Platform: Deep experience with AWS (containers and EKS, serverless, Step Functions, storage, networking, IAM) and working knowledge of Azure; infrastructure as code, CI/CD at scale, observability, and FinOps and unit cost management.
• AI Engineering Depth (mandatory and non-negotiable): Must have architected and shipped production AI systems, not merely consumed AI tools. Expected depth includes LLM application architecture, retrieval and context engineering, agentic orchestration and durable workflows, model selection and routing, evaluation harnesses (deterministic gates, LLM-as-judge, golden datasets, regression and drift detection), guardrails and prompt injection defence, cost and latency engineering, and AI governance in a regulated environment.

📌 National Lead - Digital Platforms & Consumer Technology (Pune)
🏢 Bajaj Finance
📍 Pune