Java Architect with Java, SpringBoot, React, Kafka, SNOWFLAKE, AWS/Google Cloud Platform/Azure, AI, LLM, RAG, CI/CD
Principal Software Architect Position Summary
We are seeking a Principal Software Architect to set the technical direction for a SaaS product and guide its evolution across application architecture, data platforms, integrations, and delivery practices. This is a senior technical leadership role that combines architecture and hands-on engineering judgment with cross-functional collaboration.
You will work closely with engineering, product, data, security, operations, and business teams to design scalable, secure, and resilient systems. The platform uses Java and Spring Boot, React, Kafka-based data pipelines, and Snowflake, with extensive third-party integrations. You will also help identify and responsibly apply AI and large language model technologies to product and engineering needs.
Responsibilities
Define and evolve the platform s technical architecture and long-term roadmap, aligning design decisions with product goals, scale, reliability, security, and cost
Provide technical leadership across backend services built with Java and Spring Boot and frontend applications built with React
Design scalable event-driven architectures and high-throughput data pipelines using Apache Kafka
Guide data architecture and integration patterns involving Snowflake and other analytical data systems
Lead architecture for complex third-party integrations, including API design, authentication, data mapping, reliability, versioning, and failure handling
Establish architectural standards and patterns for service boundaries, data contracts, observability, security, and performance
Strengthen CI/CD practices, deployment automation, testing strategy, and release reliability across engineering teams
Collaborate with product, data, security, operations, and engineering leaders to evaluate tradeoffs and guide technical decisions
Review designs and provide mentorship to engineers and technical leads, raising engineering quality across teams
Identify and address technical risks, scalability constraints, architectural debt, and operational bottlenecks
Evaluate AI and LLM technologies and lead their practical, secure integration into the product or engineering workflows where they provide measurable value
Communicate technical strategy, options, and tradeoffs clearly to technical and non-technical stakeholders
Required Qualifications
Significant experience designing and evolving production software architectures, including experience in a principal, staff, or equivalent senior technical leadership role
Strong hands-on background with Java and Spring Boot in distributed, production-scale systems
Experience with React and modern web application architecture
Proven experience designing event-driven systems and large-scale streaming or data pipelines using Apache Kafka
Strong understanding of cloud data warehousing concepts and practical experience with Snowflake
Demonstrated success architecting and operating integrations with multiple third-party platforms and APIs
Strong understanding of CI/CD, automated testing, deployment strategies, and production operations
Experience building SaaS products, including multi-tenancy, security, availability, scalability, and serviceability considerations
Ability to lead through technical influence and collaborate effectively across organizational boundaries
Excellent communication, decision-making, and technical documentation skills
Preferred Qualifications
Experience with AWS, Azure, or Google Cloud and cloud-native architecture
Familiarity with containers and orchestration platforms such as Docker and Kubernetes
Experience with data governance, data quality, schema evolution, and analytical modeling
Experience implementing AI or LLM-enabled capabilities in production systems
Familiarity with LLM integration patterns, evaluation, retrieval-augmented generation (RAG), prompt management, and responsible AI practices
Experience with observability platforms, distributed tracing, and reliability engineering
Knowledge of security and compliance practices relevant to SaaS products
Experience mentoring senior engineers or guiding architecture across multiple teams
What Success Looks Like
The platform s technical roadmap supports product goals and anticipated growth
Services, data pipelines, and integrations are reliable, observable, secure, and maintainable
Engineering teams use consistent architectural patterns while retaining appropriate autonomy
CI/CD and testing practices enable frequent, controlled delivery
Technical tradeoffs are understood and decisions are made collaboratively
AI and LLM capabilities are introduced where they solve clear problems and meet quality, privacy, and security expectations
