Technical Architect

Preferred Square; Gurugram District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Preferred Square is seeking a Technical Architect to steer the overall technical direction for AI-enabled products and platforms in Gurugram. You will guide Tech Leads, review critical design decisions, and address high-risk areas while ensuring that application, data, integration, cloud, security and AI decisions align across teams.

You will translate business goals into concrete architectural patterns, guardrails, and governance across distributed systems, with a focus on scalability,

Qualifications

• 9–12 years of software engineering with architecture ownership for complex production systems.
• Experience guiding multiple engineering teams or major workstreams.
• Deep knowledge of distributed systems, APIs, integration patterns, cloud architecture, security and data platforms.
• Strong understanding of enterprise AI architecture including RAG, agentic systems, observability, privacy and governance.

Responsibilities

• Lead technical discovery and define end-to-end architecture for complex products and platforms.
• Translate business goals and non-functional requirements into architectural decisions across applications, data, integration, identity, security, AI, deployment, monitoring, resilience and support.
• Define reusable patterns and reference architectures with practical engineering guardrails.
• Lead technology choices and explain trade-offs across security, scalability, maintainability, cost, delivery speed and vendor dependence.
• Design enterprise patterns for RAG, agents, orchestration, evaluation, model routing, memory, LLMOps and responsible AI.
• Review critical designs, security considerations, and production-readiness plans.
• Guide Tech Leads, resolve cross-team issues, and assist in high-risk areas when needed.
• Identify architectural risks early and agree mitigation and fallback options.
• Lead discussions with senior client, business, security, and data stakeholders.
• Support proposals, estimates, roadmaps and technical due diligence for new opportunities.
• Improve reuse across projects without imposing unnecessary processes.

Skills

Distributed systems

Cloud architecture

Architecture decisions

Leadership

AI platform patterns

Security

CI/CD

Observability

Vendor evaluation

Scalability

Education

Bachelor's or Master's in Computer Science or related field

Tools

Terraform

Kubernetes

CI/CD tooling

Job description

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.

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
• Strong 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