Data and AI Products Architect

Role Overview

This role owns the technical architecture of the Data & AI product portfolio and acts as the Technical counterpart to the Product Owner. Works with Innovation on PoC-to-product transitions and applies AI governance and Responsible AI standards. Responsible for architecting products for multi-tenancy and non-functional characteristics.

Key responsibilities

Product architecture & portfolio

• Own the target architecture for each product in the portfolio designing for reuse configurability and multi-tenancy.

• Define the shared platform layer common services components and infrastructure reusable across products and drive consolidation of duplicated capability.

• Own architecture roadmap in sync with product roadmap.

AI & GenAI solution design

• Responsible for design decisions: build vs. buy model selection fine-tuning vs. retrieval technical debt management and trade-offs.

• Design retrieval architectures (chunking embedding indexing hybrid search and re-ranking) for accuracy and latency at scale.

• Define the data architecture for AI solutions training data feature pipelines etc.

• Architect observability monitoring and drift detection

Product maturation and disposition

• Assess PoCs and early MVPs for technical viability scalability and productisation.

• Conduct product technical readiness assessments; provide the architectural basis for product disposition decisions.

Production readiness & unit economics

• Design the LLMOps/MLOps backbone for the portfolio serving versioning deployment pipelines and rollback.

• Define evaluation architecture: eval harnesses quality benchmarks regression testing.

• Own the cost model inference economics and token cost as an input to product pricing.

Safety governance & technical leadership

• Embed Responsible AI explainability and AI security standards into product designs. Design for the regulatory obligations.

• Support the Product Owner with technical input to funding pitches business cases and customer conversations.

Experience

• 1015 years in software/ML engineering and architecture with proven AI solutions in production

Expected Skills

• GenAI architecture LLMs RAG agentic patterns orchestration frameworks

• MLOps/LLMOps evaluation design model serving observability and inference cost optimisation

• Experience in architecting commercial software products - Multi-tenancy versioning and productisation of prototypes

• Working knowledge of data platforms pipelines and modelling

• Ability to connect architectural choices to unit economics profitability and time-to-market

• Guide the product development teams with implementation and standards compliance
   

Qualifications :

Educational qualification:

B.E/ or equivalent Qualification

Experience :

• 1015 years in software/ML engineering and architecture with proven AI solutions in production

Mandatory/requires Skills :

• GenAI architecture LLMs RAG agentic patterns orchestration frameworks

• MLOps/LLMOps evaluation design model serving observability and inference cost optimisation

• Experience in architecting commercial software products - Multi-tenancy versioning and productisation of prototypes

• Working knowledge of data platforms pipelines and modelling

• Ability to connect architectural choices to unit economics profitability and time-to-market

• Guide the product development teams with implementation and standards compliance

Preferred Skills :

Remote Work :

No

Employment Type :

Full-time