Principal Enterprise Architect

IndiaRemoteFull-timelead

EngineeringSoftware Architect

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Quick Summary

Overview

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal Enterprise Architect based in India.

Technical Tools

EngineeringSoftware Architect

The Principal Enterprise Architect will shape the technical vision for highly scalable, cloud-native, and AI-enabled enterprise systems. You will combine strategic architecture leadership with hands-on technical expertise to modernize platforms, improve performance, and optimize cloud costs. The role has a strong focus on AWS, distributed systems, multi-tenant SaaS architectures, data platforms, and GenAI adoption. You will work closely with engineering teams to turn architectural strategies into practical solutions through prototypes, automation, and self-service capabilities. As an AI adoption catalyst, you will help embed intelligent tools and workflows throughout the software development lifecycle while maintaining strong security and governance. This is a high-impact opportunity to influence technology direction across a global environment while mentoring teams and driving long-term architectural excellence.

Own the technical vision and architecture strategy for scalable, high-performance, and cost-efficient enterprise systems.
Define modern architecture patterns that support rapid growth, high transaction volumes, reliability, and seamless scalability.
Design and optimize multi-tenant SaaS platforms with strong configurability, performance, and operational efficiency.
Develop self-service capabilities that reduce engineering effort, including workflow designers, rules engines, reporting solutions, and AI-enabled tools.
Lead cloud cost optimization initiatives covering infrastructure, compute resources, model execution, and operational efficiency.
Partner with cloud support and solution architecture teams to optimize infrastructure and leverage emerging cloud capabilities.
Architect high-scale distributed data processing platforms supporting both batch and real-time workloads.
Optimize data storage, retrieval, processing, governance, security, and accessibility for analytics, machine learning, and business use cases.
Guide engineering teams on microservices, event-driven architectures, cloud-native patterns, scalability, and architectural best practices.
Validate architectural decisions through hands-on prototyping, proof-of-concepts, and technical experimentation.
Champion the adoption of GenAI, LLMs, and agentic workflows across the software development lifecycle while maintaining appropriate security, governance, and cost controls.
Lead architectural governance and cross-functional reviews, identifying technical debt, resolving complex trade-offs, and maintaining long-term system coherence.
Establish and promote architectural standards across product teams and mentor engineering leaders on effective technical decision-making.

Requirements

~2 min read

12+ years of hands-on experience in system architecture, data engineering, cloud engineering, or technical leadership roles.
Extensive experience designing multi-tenant architectures and configurable SaaS platforms.
Deep hands-on expertise with AWS, including technologies such as EKS, IAM, Lambda, and cloud networking; professional GCP experience is a strong plus.
Strong knowledge of distributed systems, microservices, event-driven architectures, caching strategies, and high-scale transactional platforms.
Hands-on understanding of AI/ML model execution, including inference performance, cost trade-offs, and optimization strategies.
Experience with infrastructure automation and modern engineering practices using technologies such as Terraform, CI/CD, Kubernetes, and Docker.
Expert-level Java development skills and strong Python capabilities, with knowledge of JavaScript/TypeScript and Kotlin.
Proven experience leading architectural review processes, establishing engineering standards, and driving technical alignment across teams.
Demonstrated success integrating GenAI and machine learning approaches into software development processes.
Strong strategic stakeholder management skills, with the ability to communicate complex technical concepts and align diverse teams around common objectives.
Experience conducting or contributing to complex financial and Total Cost of Ownership (TCO) analysis for enterprise technology.
Strong strategic thinking combined with a hands-on, pragmatic, and execution-oriented mindset.
Ability to coach, mentor, influence, and bring engineering teams along through technology transformation.
Experience working in fast-paced environments where multiple priorities require sound architectural judgment and decisive execution.