Solutions Engineer

Ridecell World's Leading Fleet Intelligence Platform

Solutions Engineer •DE Job type Full-time Role Sales Experience 3+ years Visa US citizenship/visa not required

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About the role You will launch Ridecell at some of the largest fleet and leasing businesses in Europe - names like Arval BNP Paribas Group and KINTO by Toyota - turning their most complex operational processes into scalable, automated solutions. You’ll do it on a platform that already processes 12M+ events a day across 500K+ managed assets in 14+ countries, deployed anywhere from multi-tenant SaaS to fully sovereign inside the customer’s perimeter.

Our Solutions Team owns workflow-orchestration, data-pipeline, and AI projects end-to-end. We are the bridge between customer business teams, their core leasing systems (e.g. Sofico Miles, Odessa), suppliers, and our internal Engineering, Product, QA, Launch, Customer Success, and Sales functions.

As a Solutions Engineer, you will translate complex business processes into scalable Ridecell solutions: define future-state processes, design lifecycle and integration concepts, align API specifications, and shepherd the work all the way into stable production operations. Why This Role

• Real ownership. You lead the engagement, set the technical direction, and have a decisive voice in whether a launch is ready.
• Strategic accounts. You work directly with category-defining European fleet and leasing customers, not generic mid-market deployments.
• Product influence. Gaps and patterns you spot in the field feed straight back into the Ridecell roadmap - you don’t just file tickets, you shape them.
• A real team behind you. You partner day-to-day with Engineering Leads, Product Managers, QA, Launch, Customer Success, and customer PMs - not a solo hero role.
• AI as a first-class tool, not a slide. You’ll embed AI into customer workflows and into how the Solutions team itself operates.

Responsibilities

• Own the engagement. Lead the workstream end-to-end, coordinating customer business teams, core leasing system teams, suppliers software architects, and internal stakeholders.
• Discover. Map current-state business and supplier processes, operational constraints, IT capabilities, and integration readiness.
• Design the solution. Run process-mapping workshops to define future-state processes and scope. Translate requirements into lifecycle architecture, automation logic, data flows, supplier interactions, exception handling, and configuration models - including where AI agents or models meaningfully replace or augment a human step.
• Specify and align. Design the integration footprint across the customer’s system landscape - telematics, ERP, OEM portals, core leasing systems, maintenance, invoicing, insurance, and more - and define how data is harmonized into a single intelligence layer. Specify inbound/outbound API contracts, payloads, lifecycle triggers, business events, and error-handling rules. Maintain the supporting integration documentation and test collections. Facilitate technical alignment with customer IT, supplier developers, and internal Product, Engineering, and QA.
• Shape the backlog. Turn product gaps, configuration needs, and custom developments into well-scoped engineering stories across frontend, backend, data pipelines, integrations, dashboards, and AI features. Partner with Engineering Leads and customer PMs on sizing and planning.
• Drive build, test, and data readiness. Equip Engineering with the business context and test scenarios they need; plan internal, supplier, and end-to-end testing; and lead data initialization - mapping legacy statuses, reviewing extraction logic, and challenging data quality.
• Enable the customer. Define and validate operational and KPI dashboards, and deliver customer and train-the-trainer enablement covering usage, exception handling, operations, and how to work alongside the AI agents in their workflow.
• Launch and stabilize. Prepare production tenants, run go/no-go reviews, provide on-site support during the first days after launch, and transition cleanly into hypercare.

Requirements

• Experience. 3+ years in Solution Engineering, Solution Architecture, Technical Project Delivery, or Technical Consulting in complex enterprise software environments, with a proven track record leading projects end-to-end through to stable production.
• Domain. Hands-on experience with configurable enterprise platforms - data integration, lifecycle architecture, workflow automation, AI agents, or operational intelligence systems - and a solid grounding in SaaS architecture, enterprise integrations, and data models.
• Process and design. You can read current-state processes, define future-state operating models, and translate business needs into clean functional and technical designs.
• Delivery craft. You write crisp user stories, acceptance criteria, integration specs, test cases, and operational handover docs, and work fluently in standard agile delivery tooling.
• Technical fluency. Comfortable in Python and SQL, designing and debugging REST API integrations (webhooks, JSON payloads, auth, OpenAPI), and reasoning about data pipelines. You can roll up your sleeves to configure a tenant, validate a lifecycle, test an endpoint, or chase down a data-quality issue yourself.
• Practical experience in AI. You actively use coding agents and other AI tools to multiply your own output. You can also reason at a platform level about embedding AI into the solutions we deploy - judging where it genuinely improves an operational workflow versus where it doesn’t, designing for human-in-the-loop and graceful failure, and anticipating what AI adoption means for end-user trust, change management, and training inside the customer’s operations team.
• Ownership. High follow-through, especially in complex multi-party deliveries where things rarely go to plan.
• Communication and stakeholder management. Equally clear with business users, developers, suppliers, and executives. You challenge requirements, control scope, clarify responsibilities, and drive open topics to resolution across many parties.
• Languages. Fluency in German and English required; additional European languages are a strong plus.
• Travel. ~10% to customer and supplier sites for workshops, alignment, testing, and launches.
• We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.

About Ridecell Ridecell is the world’s leading fleet intelligence platform. We bring AI to auto-leasing and finance companies - and to the fleets and consumers they serve - by turning 100+ fragmented systems (telematics, ERP, OEM portals, maintenance, invoicing, insurance) into a single intelligence layer that doesn’t just surface data, but drives decisions. Our Five Intelligence Modules - Operational, Asset, Supplier, Spend, and Client - are powered by specialized AI agents that process 12M+ events a day across 500K+ managed assets in 14+ countries. The platform ships in three deployment modes (managed SaaS, dedicated single-tenant, and fully sovereign inside the customer’s perimeter), so our teams get to work across the full spectrum of real-world enterprise AI deployment. Our customers include Arval BNP Paribas Group, Merchants Fleet, and KINTO by Toyota. Ridecell is headquartered in California, with offices in Paris, Bordeaux, Madrid, and Pune (India). For more information, visit www.ridecell.com.