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EVPassport · 4 weeks ago

Lead Engineer/Solution Architect

United States

Contract

Remote

Senior Level, Lead/Staff

8+ years exp

EVPassport is an EV Charging hardware and software platform focused on providing seamless payment experiences for electric vehicle charging. The Lead Engineer/Solution Architect will define and own the technical architecture to support operational functions, ensuring data consistency and enabling automation and AI-driven intelligence across the company.

Charging InfrastructureElectric VehicleHardwareInformation TechnologyRenewable EnergySoftware

Responsibilities

Define, design, and own the end-to-end architecture for EVPassport’s internal operational systems, data infrastructure, and integration layer

Build and govern a unified internal source-of-truth architecture, ensuring data consistency, lineage, and reliability across all business systems (e.g., CPMS, ERP, CRM, payments, support)

Architect scalable internal infrastructure—including APIs, event-driven services, data schemas, pipelines, and metadata frameworks—to support AI readiness, analytics, and automation

Drive the creation of reusable internal data models, shared services, and connectors that standardize how operational data flows across systems

Ensure our infrastructure is highly performant, resilient, secure, and designed to support rapid growth with minimal friction

Lead the design, governance, and evolution of internal and external APIs to support clean, normalized data exchange across platforms

Define integration patterns and frameworks for data ingestion, transformation, and synchronization between EVPassport systems and third parties

Oversee the data architecture that powers BI, AI/ML, and real-time operational insights, including schemas, storage strategy, and event architectures

Ensure data flows meet enterprise-grade expectations for accuracy, observability, compliance, and security

Provide hands-on architectural leadership to engineering teams, shaping best practices around service design, CI/CD, infrastructure-as-code, and systems observability

Conduct deep technical reviews, guide high-impact implementation decisions, and deliver proof-of-concepts to de-risk architectural choices

Own platform-wide non-functional requirements (NFRs) such as reliability, scalability, throughput, latency, failover design, and cost efficiency

Evaluate and introduce new infrastructure technologies, automation tools, and cloud capabilities that accelerate development velocity and reduce operational overhead

Serve as the technical bridge between Product, Engineering, Data, and Operations teams—translating requirements into system designs and long-term architectural strategy

Partner with business leaders to ensure operational workflows, data structures, and platform capabilities scale with EVPassport’s growth

Collaborate with Data, AI, and Engineering teams to ensure the platform supports autonomous operations, predictive insights, and next-generation customer experiences

Additional projects as may be assigned by the Company

Qualification

Microservices architectureDistributed systemsAPI designGovernanceData modelingCloud infrastructure AWSCloud infrastructure GCPCloud infrastructure AzureEvent-driven architecturesData pipelinesInfluencing stakeholdersExperience in EV chargingIoT protocolsExceptional communicationCross-functional leadership

Required

8+ years in Software Development, Platform Engineering, or Systems Architecture, ideally within high-growth SaaS, PaaS, or data-intensive environments

3+ years in a Lead Engineer, Principal Engineer, or Solution Architect role, driving architecture for distributed systems and complex integrations

Expertise in designing and operating microservices, distributed systems, event-driven architectures, and modern cloud infrastructure (AWS, GCP, or Azure)

Proven experience designing, governing, and scaling internal and external API ecosystems (REST, GraphQL, or event-driven APIs)

Strong understanding of data modeling, data pipelines, metadata management, schema governance, and building clean, reliable datasets at scale