Description

Key Responsibilities

1. Product & Technology Architecture

• Own the end-to-end product architecture and technology roadmap.
• Define scalable, secure, modular and enterprise-grade architectures.
• Translate business requirements into product capabilities, technical architecture and solution blueprints.
• Design AI/ML architecture covering LLMs, GenAI, RAG, NLP, conversational AI, multimodal AI, AI agents and AI evaluation.
• Drive API-first, microservices, event-driven and cloud-native architecture.
• Ensure scalability, availability, reliability, observability, performance and maintainability.
• Define integration architecture across internal platforms, external products and third-party services.

2. Product Management

• Translate customer and business requirements into product capabilities, roadmap and technical priorities.
• Drive product backlog, feature prioritization and release planning with Product and Business teams.
• Perform competitive benchmarking and product capability assessment.
• Identify product gaps and define capabilities required to make products enterprise-ready and market competitive.
• Drive Build vs. Buy vs. Integrate decisions based on business value, technical feasibility, cost, scalability and time-to-market.
• Participate in customer discussions, discovery sessions and product demonstrations.

3. AI & Intelligent Product Capabilities

The candidate should have a strong understanding of:

• Generative AI and LLM-based applications
• AI Agents and Agentic workflows
• RAG and knowledge-based AI
• NLP and conversational AI
• Multimodal AI
• AI-based recommendations and decisioning
• AI evaluation, benchmarking and quality frameworks
• Human-in-the-loop AI
• Model selection, orchestration and optimization
• AI governance, responsible AI and model monitoring

4. Enterprise Platform Capabilities

Drive architecture and productization of:

• Multi-tenancy and tenant isolation
• RBAC and enterprise identity integration
• API gateway and partner integrations
• Enterprise integration frameworks
• Workflow and orchestration engines
• Analytics, dashboards and reporting
• Audit trails and data lineage
• Consent, privacy and data retention
• Security and compliance
• Monitoring, observability, SLA and production support architecture
• High availability, disaster recovery and business continuity

5. Product Engineering Leadership

• Work closely with Engineering, AI/ML, UX, QA, DevOps, Security and Product teams.
• Establish architecture standards, design principles and technical governance.
• Review technical designs and ensure alignment with product strategy and roadmap.
• Mentor architects, senior engineers and technical leads.
• Drive technical debt reduction, modernization and platform scalability.
• Ensure engineering execution remains aligned with product outcomes.

Required Skills

Architecture

• Distributed systems and microservices
• Cloud-native architecture – AWS / Azure / GCP
• REST APIs, event-driven architecture and API gateways
• Databases, caching, messaging and data platforms
• Kubernetes and containerization
• CI/CD, DevSecOps, observability and SRE principles
• Enterprise integration and solution architecture

AI / GenAI

• LLMs and Generative AI
• RAG and vector databases
• AI Agents / Agentic AI
• NLP and conversational AI
• Multimodal AI
• AI evaluation and benchmarking
• Model governance and responsible AI
• AI/ML lifecycle and MLOps

Data

• Data architecture and data engineering
• Structured and unstructured data
• Data pipelines and data processing
• Data quality, lineage and governance
• Real-time and batch processing
• Knowledge graphs / vector search is desirable

Product Management

• Product lifecycle management
• Product strategy and roadmap
• Product backlog and prioritization
• Agile / Scrum
• Customer discovery and requirement analysis
• Competitive analysis
• Build vs. Buy vs. Integrate decisions
• Enterprise SaaS product management
• Business case and ROI evaluation

Preferred Experience

• Experience building and scaling enterprise SaaS, AI/ML, GenAI or platform products.
• Experience working across Product, Engineering, AI/ML and Business functions.
• Experience taking products from concept → architecture → MVP → enterprise production → scale.
• Experience with complex enterprise integrations and third-party ecosystems.
• Experience evaluating competing products and defining product differentiation and technology strategy.
• Experience in multiple business domains is preferred, enabling the candidate to architect and productize solutions across different industries

Key Skills

Education

Any Gradute