The Technical Architect is responsible for the overall technical direction of complex AI-enabled products and platforms. You will work across teams and client workstreams, making sure that application, data, integration, cloud, security, and AI decisions fit together. This is not a role that sits outside delivery. You will guide Tech Leads, review the most important design choices, and step into difficult technical areas when the team needs experienced judgement.

What You'll Do

• Lead technical discovery and define the end-to-end architecture for complex products and platforms • Turn business goals and non-functional requirements into clear decisions across applications, data, integration, identity, security, AI, deployment, monitoring, resilience, and support

• Define reusable patterns, reference architectures, and practical engineering guardrails for project teams

• Lead technology choices and explain the trade-offs across security, scalability, maintainability, cost, delivery speed, portability, and vendor dependency

• Design enterprise patterns for RAG, agents, orchestration, evaluation, model routing, memory, LLMOps, and responsible AI

• Review critical solution designs, architecture decisions, security considerations, and production-readiness plans

• Guide Tech Leads, resolve cross-team design issues, and work directly on high-risk or technically difficult areas when required

• Identify architectural risks early and agree practical mitigation and fallback options

• Lead technical discussions with senior client, business, security, data, and technology stakeholders

• Support proposals, estimates, implementation roadmaps, and technical due diligence for new opportunities





• Improve consistency and reuse across projects without imposing unnecessary process

Requirements

Experience • A bachelor's or master's degree in computer science or a related field, or equivalent practical experience

• 9 to 12 years of software engineering experience, including ownership of architecture for complex production systems

• Experience guiding multiple engineering teams, systems, or major workstreams

• Deep knowledge of distributed systems, APIs, integration patterns, cloud architecture, security, data platforms, and modern application development

• Robust understanding of enterprise AI architecture, including RAG, agentic systems, evaluation, observability, privacy, governance, and operational controls

• A track record of making and explaining architectural trade-offs to both engineers and senior stakeholders

Technical Depth

• Azure and AWS architecture across compute, containers, serverless, networking, identity, security, data, AI, monitoring, and cost management

• Microservices and modular monoliths, event-driven architecture, queues, caching, API management, and distributed-system reliability

• Identity and access management, secrets and key management, network controls, threat modelling, auditability, privacy, and software supply-chain security

• AI platform patterns including model gateways, provider abstraction, vector search, content ingestion, evaluation pipelines, tracing, guardrails, and human oversight

• Platform engineering practices including CI/CD, infrastructure as code, environment strategy, service-level objectives, disaster recovery, performance engineering, and FinOps

• Ability to produce architecture diagrams, decision records, standards, reference implementations, and production-readiness criteria that teams can use

📌 Technical Architect (Gurugram)
🏢 Preferred Square
📍 Gurugram