Technical Architect - AI

The Technical Architect will independently design and deliver enterprise AI platform solutions and agentic AI architectures. The role focuses on defining architecture patterns, guiding engineering teams, and ensuring scalable, secure, and production-ready AI implementations. Primary FocusAgentic AI architecture, enterprise AI platform design, integration/data architecture, security/compliance, responsible AI, and reusable solution blueprinting.

Responsibilities:

• Lead the architecture, design, and delivery of enterprise-scale Agentic AI solutions.
• Design end-to-end agentic AI solutions, including agent topology, memory and context management, orchestration frameworks, and tool integrations.
• Build AI platform architectures leveraging vector stores, embedding pipelines, model routing, LLM gateways, and inference optimization.
• Define integration architectures across enterprise platforms, including SAP, Salesforce, ServiceNow, and Appian.
• Implement security, Responsible AI, compliance, and governance controls.
• Create reusable architecture patterns, solution blueprints, and technical standards.
• Provide hands-on technical guidance to engineering and delivery teams.
• Support scalable deployment of AI and GenAI solutions across client environments.

Requirements:

• Qualifications: BE/BTech/MTech.
• Years of Experience: 12 to 16 years.
• Language Ability: English (International) - Intermediate.
• Professional Skills: Solution Architecture and Technical Leadership, Strategic Problem Solving, Cross-Functional Collaboration, Stakeholder and Client Engagement, Communication and Presentation Skills, Team Leadership and Mentoring, Innovation and Continuous Improvement, Technology Advisory, and Decision Making.

Required skills:

• Agentic AI Architecture: Agent Architecture Design, Multi-Agent Systems and Coordination, Agent Memory and Context Management, Agent Orchestration and Workflow Design, Tool Integration and Failover Strategies.
• Enterprise AI Platform Design: Vector Databases and Semantic Search, Embeddings and Retrieval Frameworks, LLM Gateway and Model Routing, AI Inference Optimization, AI Cost Governance and Monitoring, Enterprise AI Platform Architecture.
• Integration and Data Architecture: SAP, Salesforce, ServiceNow, and Appian Integration; API Architecture and Contract Design; Event-Driven Architecture; Kafka/MSK and Streaming Platforms; Data Architecture and Security Design; Enterprise Integration Patterns.
• Security and Responsible AI: OAuth and Identity Management, Azure AD / Enterprise Authentication, Responsible AI Guardrails, Bias Detection and Risk Mitigation, Audit Logging and Traceability, GDPR, SOX, and Regulatory Compliance, Data Privacy and Sovereignty Management.
• Reusable Blueprinting: Enterprise Reference Architectures, Reusable AI Solution Patterns, Platform Standards and Governance, Scalable AI Design Frameworks, Architecture Best Practices and Guidelines, Enterprise AI Modernization Strategies.