Professional Experience: At least 10 years of software engineering experience, including significant expertise in platform architecture, distributed systems, enterprise software, or related technical
Enterprise Platform Architecture: Proven experience architecting and delivering enterprise-scale SaaS platforms or cloud-native applications, with a strong understanding of scalability, reliability, p
Cloud and Infrastructure Engineering: Deep knowledge of cloud services, containerization, Kubernetes, CI/CD pipelines, infrastructure as code, deployment automation, and observability practices.
API Design and Integration: Strong familiarity with REST APIs, GraphQL, event streaming, and modern integration frameworks, with demonstrated experience designing secure integrations across multiple e
Enterprise Application Ecosystems: Experience integrating complex business and engineering platforms, ideally including Autodesk, Esri ArcGIS, Bentley, Deltek Vantagepoint, or enterprise content manag
Data Architecture: Understanding of modern data architectures, including data lakes, lakehouses, data pipelines, data integration patterns, and API-based data access.
AI and Machine Learning Architecture: Working knowledge of AI/ML application architecture, including large language model integration, retrieval-augmented generation, vector search, AI orchestration,
Security and Identity Management: Strong understanding of enterprise security architecture, identity and access management, authentication, authorization, and enterprise data protection principles.
Full description
This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Principal Platform Architect based in the United States.
The Principal Platform Architect will define and build the technical foundation of a next-generation digital platform supporting enterprise-wide innovation and business growth. This senior technical leadership role combines hands-on software engineering, cloud-native architecture, enterprise integration, data platform collaboration, and AI enablement. You will establish scalable, secure, and reusable platform capabilities that empower engineering teams to deliver reliable digital products efficiently. Working closely with product, engineering, data, IT, security, and business stakeholders, you will translate complex requirements into practical architectural solutions. The role emphasizes technical execution, pragmatic decision-making, and continuous improvement rather than architecture design alone. You will also shape the long-term platform roadmap while helping teams solve complex implementation challenges and adopt modern engineering practices. This is an opportunity to influence enterprise technology strategy and build innovative solutions that support a growing, distributed organization.
Accountabilities:
Platform Architecture and Strategy: Define, implement, and continuously evolve the overall platform architecture, ensuring scalability, security, reliability, maintainability, and flexibility across digital products and enterprise systems.
Shared Platform Services: Design and develop reusable platform capabilities, including identity and access management, APIs, notification services, workflow orchestration, and common application services that accelerate product development.
Cloud-Native Engineering: Establish architectural standards and engineering practices for cloud infrastructure, containerization, CI/CD pipelines, infrastructure as code, observability, and deployment automation.
Enterprise Systems Integration: Design and implement secure, scalable integration patterns connecting enterprise applications, engineering systems, content management platforms, and digital products across multiple business units.
Data Architecture Collaboration: Partner with data engineering teams and data architecture leaders to enable consistent, secure, and efficient access to enterprise data through shared services, APIs, and modern integration patterns.
AI and Intelligent Automation Enablement: Define reusable architectural capabilities for integrating generative AI, AI agents, large language models, retrieval-augmented generation (RAG), vector search, and intelligent automation into digital applications.
Technical Problem-Solving: Demonstrated ability to evaluate architectural trade-offs, troubleshoot complex engineering challenges, and deliver pragmatic solutions that meet immediate requirements with
Hands-On Engineering Approach: Ability to work directly with engineering teams, validate architectural decisions through implementation, and guide technical execution rather than relying solely on hig
Strategic Thinking: Strong ability to develop technical roadmaps, establish architectural standards, anticipate scalability challenges, and align platform investments with business and product priorit
Communication and Collaboration: Excellent communication, stakeholder management, and collaboration skills, with the ability to explain complex technical concepts clearly and build consensus across en
Adaptability and Innovation: A forward-thinking mindset, a commitment to continuous improvement, and the ability to introduce modern technologies and engineering practices in a growing enterprise envi
Work Arrangement: Ability to work effectively in a fully remote position based in the United States while collaborating with distributed technical and business teams.
Hands-On Technical Leadership: Work directly with engineering teams on solution design, architecture reviews, technical decision-making, code-level challenges, and complex implementation issues, ensuring architectural recommendations translate into production-ready capabilities.
Architecture Roadmap Development: Build and maintain an incremental platform roadmap that balances immediate business and product delivery needs with long-term scalability, maintainability, and technical sustainability.
Security and Reliability: Collaborate with IT and security stakeholders to implement enterprise-grade security controls, identity management, authorization policies, data protection, monitoring, and operational readiness practices.
Cross-Functional Collaboration: Work closely with product, engineering, data, IT, security, and business teams to translate business objectives into effective technical solutions and align architecture decisions with organizational priorities.
Engineering Standards and Best Practices: Establish consistent architectural patterns, technical guidelines, and reusable implementation approaches that improve engineering productivity, system interoperability, and overall platform quality.
Continuous Improvement and Innovation: Evaluate emerging technologies, identify opportunities to modernize existing systems, and introduce practical architectural improvements that support digital transformation and future platform capabilities.
Requirements:
Professional Experience: At least 10 years of software engineering experience, including significant expertise in platform architecture, distributed systems, enterprise software, or related technical disciplines.
Enterprise Platform Architecture: Proven experience architecting and delivering enterprise-scale SaaS platforms or cloud-native applications, with a strong understanding of scalability, reliability, performance, and maintainability.
Cloud and Infrastructure Engineering: Deep knowledge of cloud services, containerization, Kubernetes, CI/CD pipelines, infrastructure as code, deployment automation, and observability practices.
API Design and Integration: Strong familiarity with REST APIs, GraphQL, event streaming, and modern integration frameworks, with demonstrated experience designing secure integrations across multiple enterprise systems and data sources.
Enterprise Application Ecosystems: Experience integrating complex business and engineering platforms, ideally including Autodesk, Esri ArcGIS, Bentley, Deltek Vantagepoint, or enterprise content management systems.
Data Architecture: Understanding of modern data architectures, including data lakes, lakehouses, data pipelines, data integration patterns, and API-based data access.
AI and Machine Learning Architecture: Working knowledge of AI/ML application architecture, including large language model integration, retrieval-augmented generation, vector search, AI orchestration, and the development of AI-enabled applications.
Security and Identity Management: Strong understanding of enterprise security architecture, identity and access management, authentication, authorization, and enterprise data protection principles.
Technical Problem-Solving: Demonstrated ability to evaluate architectural trade-offs, troubleshoot complex engineering challenges, and deliver pragmatic solutions that meet immediate requirements without compromising long-term platform goals.
Hands-On Engineering Approach: Ability to work directly with engineering teams, validate architectural decisions through implementation, and guide technical execution rather than relying solely on high-level design documentation.
Strategic Thinking: Strong ability to develop technical roadmaps, establish architectural standards, anticipate scalability challenges, and align platform investments with business and product priorities.
Communication and Collaboration: Excellent communication, stakeholder management, and collaboration skills, with the ability to explain complex technical concepts clearly and build consensus across engineering, product, data, IT, security, and business teams.
Adaptability and Innovation: A forward-thinking mindset, a commitment to continuous improvement, and the ability to introduce modern technologies and engineering practices in a growing enterprise environment.
Work Arrangement: Ability to work effectively in a fully remote position based in the United States while collaborating with distributed technical and business teams.
Benefits:
Competitive Annual Salary: Published annual compensation range of $161,000–$190,000, with final compensation determined by experience, skills, qualifications, internal equity, and geographic location.
Fully Remote Work: Opportunity to work remotely from within the United States.
Technical Leadership Opportunities: Shape the architecture and evolution of a next-generation enterprise digital platform while influencing major engineering decisions.
Professional Development: Access to diverse career paths and opportunities to expand expertise across platform engineering, cloud architecture, enterprise integration, data platforms, and AI-enabled applications.
Innovation and Technical Ownership: Build reusable platform capabilities, establish engineering standards, and help drive long-term technology strategy.
Cross-Functional Collaboration: Work with multidisciplinary teams across engineering, product, data, IT, security, and business functions.
Meaningful Industry Impact: Contribute to digital solutions that support infrastructure consulting and help address complex challenges involving sustainability, resilience, and community development.
Growth-Oriented Environment: Join an expanding organization that emphasizes talent development, career progression, and long-term professional growth.
Diverse Career Opportunities: Potential career paths across technical leadership, engineering, project management, business management, business development, and operations.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
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