The Principal Architect is a senior technical leader responsible for defining and driving the architecture of enterprise-grade software, data, and AI solutions. This role combines deep software engineering expertise, enterprise architecture capabilities, and strategic technical leadership to deliver scalable, secure, resilient, and high-performance platforms.
The Principal Architect will guide architectural decisions across AI-enabled applications, data platforms, cloud-native systems, and enterprise integrations. Working closely with engineering, product, and business leaders, this role translates business objectives into practical technical solutions, establishes engineering standards, and supports the delivery of innovative products and platforms.
Define and drive enterprise architecture strategies, reference architectures, design patterns, and technical standards aligned with business objectives and technology roadmaps.
Architect scalable, secure, and resilient software platforms, distributed systems, microservices, cloud-native applications, and enterprise integration solutions.
Lead the design of AI and Generative AI solutions, including LLM integrations, AI agents, RAG pipelines, model orchestration, and intelligent workflow automation.
Design enterprise data architectures and integration frameworks supporting data ingestion, transformation, quality, governance, APIs, and interoperability across systems.
Partner with engineering, product, security, and business stakeholders to translate requirements into technical designs while balancing scalability, performance, security, cost, and delivery timelines.
Establish best practices for software quality, automated testing, CI/CD, observability, fault tolerance, production readiness, and operational reliability.
Evaluate emerging technologies, cloud services, frameworks, and third-party solutions to guide technology selection, build-versus-buy decisions, and platform modernization.
Lead architecture reviews, technical assessments, and complex design decisions while identifying risks, performance bottlenecks, and opportunities to reduce technical debt.
Define security and governance standards covering identity management, data privacy, access controls, responsible AI, and production system reliability.
Mentor engineers and technical leads, document architectural decisions, and communicate technical strategies and trade-offs to executive and cross-functional stakeholders.