DomainTechnical Architect

Enterprise AI strategy & architecture leader Multi-cloud Generative AI / Agentic AI

Job Type Full-Time

Experience 1216 years overall; at least 5 years in Generative AI / Agentic AI with significant enterprise architecture and production delivery experience

Locations Noida Hyderabad Chennai Bangalore Pune

Primary Focus Enterprise AI strategy solution architecture architecture governance technology standards and strategic technical leadership

We are looking for a Senior AI Architect to define the enterprise architecture and technology strategy for Generative AI and Agentic AI solutions across strategic customer programs and organizational platforms. The Senior AI Architect is the senior technical authority who establishes target architectures makes cross-platform technology decisions leads architecture governance shapes reusable reference patterns and drives complex AI programs from strategy through production at scale.

• Senior enterprise AI architect and technical authority
• Owns target-state architecture and strategic technology decisions
• Leads architecture governance and influences platform roadmap
• Provides technical leadership across architects FDEs engineering and customer teams

• 55% architecture strategy and technology decisions
• 25% customer and executive stakeholder leadership
• 20% architecture governance mentoring and technical oversight

• Own the overall AI architecture strategy for strategic enterprise programs from business vision and discovery through production scale-out and operational maturity.
• Lead executive and senior-technical stakeholder discussions to establish the AI vision target architecture investment priorities technical roadmap and transformation approach.
• Define enterprise reference architectures and standards for Generative AI Agentic AI multi-agent systems RAG model integration AI platforms and enterprise AI applications.
• Lead architecture decisions across GCP Azure AWS OpenAI and Anthropic Claude selecting platforms and patterns based on business value technical fit security residency performance operational model and cost.
• Define strategic architecture for agent platforms including agent orchestration Planner/Critic/Supervisor/Orchestrator patterns domain agents Skills tools MCP memory/state workflow management and human-in-the-loop controls.
• Define enterprise AI data and knowledge architecture spanning structured/unstructured data ingestion processing search vector stores knowledge graphs where required retrieval reranking access controls and evaluation.
• Establish architecture principles for model strategy including model selection routing fallback fine-tuned/specialized models SLM/LLM usage context management caching and AI FinOps.
• Define enterprise security Responsible AI and governance architecture including identity authorization data protection privacy guardrails auditability model risk policy enforcement and human approvals.
• Define enterprise AgentOps and AI operations architecture covering observability evaluation quality management tracing logging cost monitoring incident management model/prompt/version management and continuous improvement.
• Define target-state architecture and phased roadmaps covering MVP production scale-out platform standardization and BAU operating model.
• Establish architecture review design assurance technology standards reference patterns and decision governance for AI programs.
• Review and approve high-level architecture integration architecture security architecture deployment architecture and major technical design decisions produced by AI Architects FDEs developers and partner teams.
• Lead architectural assessment of complex customer requirements and determine where capabilities should be standardized productized bought or built.
• Drive reusable architecture patterns and platform capabilities across customer programs and work with Product and Platform Engineering teams to influence roadmap priorities.
• Lead complex architecture escalations and provide direction for major production incidents systemic reliability issues and cross-platform technical challenges.
• Support proposals RFPs solution estimations technical due diligence POCs business cases and strategic customer engagements.
• Mentor AI Architects Senior FDEs FDEs and engineering leads; establish architecture excellence and reusable engineering practices across the organization.
• Represent the AI architecture function in customer governance forums architecture review boards technology councils and strategic planning sessions.

• Deep software engineering and enterprise solution architecture experience with the ability to guide and challenge production implementations.
• Extensive hands-on experience with Generative AI LLMs RAG agentic AI multi-agent architectures tool use evaluation and enterprise AI application design.
• Strong experience with multiple AI/cloud platforms or demonstrated ability to design platform-neutral architectures across hyperscaler and model-provider ecosystems.
• Deep understanding of enterprise architecture across application data integration cloud security networking and operations.
• Strong experience designing enterprise AI platforms reusable agent frameworks integration patterns and production operating models.
• Strong understanding of AI security Responsible AI governance privacy compliance model risk and enterprise controls.
• Strong experience with AI observability evaluation AgentOps production reliability and operational governance.
• Strong understanding of cloud-native architecture Kubernetes/serverless platforms CI/CD Infrastructure-as-Code and enterprise landing zones.
• Strong customer-facing leadership skills and ability to influence senior technical and business stakeholders.
• Demonstrated ability to make architecture decisions under ambiguity and communicate complex trade-offs clearly.

• Deep experience across two or more of GCP Azure AWS OpenAI or Anthropic Claude.
• Experience establishing enterprise AI reference architectures platform standards architecture review boards and technology governance.
• Experience with MCP A2A enterprise agent interoperability and multi-agent platform strategy.
• Experience with OpenTelemetry and AI observability/evaluation platforms such as Cloud Observability Azure Monitor/Application Insights CloudWatch LangSmith Arize or equivalent.
• Experience with enterprise security architecture Zero Trust private connectivity data residency and regulatory requirements.
• Experience with AI FinOps model strategy platform consolidation vendor evaluation and total-cost-of-ownership analysis.
• Experience leading large-scale POCs pilots MVPs production rollouts RFPs transformation programs and strategic enterprise accounts.

• Bachelors or Masters degree in Computer Science Engineering Information Technology or related field.
• 1216 years of overall software engineering cloud engineering enterprise architecture or equivalent technical experience.
• At least 5 years of practical Generative AI / Agentic AI experience including enterprise production delivery.
• Demonstrated track record of owning architecture for multiple complex enterprise technology or AI programs.
• Demonstrated experience leading senior customer engagements architecture governance and cross-functional technical teams.

• Strong enterprise architecture and strategic thinking combined with practical engineering judgment.
• Able to define a long-term architecture while maintaining a pragmatic path from MVP to production scale.
• Strong executive presence and ability to build trust with customers and internal leadership.
• Highly effective at resolving cross-team architectural conflicts and driving decisions to closure.
• Strong mentoring influence and architecture leadership capability.
• Continuously evaluates emerging AI technologies and translates relevant advances into practical enterprise architecture patterns.