Immediate Need - Reading, PA - Penske - Onsite - 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
