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We are hiring a Senior Manager, Engineering to lead that platform and the team behind it.
This is a hands-on engineering leadership role. You will spend real timeinarchitecture, design review, and the code. We are not looking for someone to inherit a platform and keep it running as it is. We are looking for a leader who will assess where the platform stands, define where it needs to go, and drive it there in partnership with architecture, infrastructure, security, and the product teams who build on it.
Whatyou'llown
Domain
Scope
Platform architecture
The end-to-end technical direction of the platform, its service boundaries, and the contracts product teams build against
Embedded analytics
Self-service reporting, dashboarding, and query capabilities delivered inside our products
Applied AI
Conversational and agentic experiences, retrieval-augmented generation, natural-language data access, and the frameworks that make them repeatable across products
Workflow automation
Configurable automation capabilities exposed to product teams and, through them, to customers
Multi-tenancy & access
Tenant isolation, identity integration, authorization, and data access controls across every capability the platformprovides
Delivery & operations
Cloud infrastructure, continuous delivery, release safety, observability, performance, and cost
Team
Hiring, coaching, and technical calibration of the platform engineering team, including operational ownership
Whatyou'lldo
Set and own the platform's technical direction.Produce a clear-eyed assessment of the current architecture and a sequenced plan to the target state. Make the trade-offs explicit and defend them.
Treat the platform as a product.Define what it offers, who consumes it, and where the boundary sits between platform and product. Makeadoptiona documented, repeatable path rather than a bespoke project each time.
Deliver analytics and AI capabilities that products can actually ship on.Balance capability, governance, performance, and cost with the discipline that enterprise customers and their data require.
Raise the engineering bar on delivery.Automated, safe, observable releases. Design review that improvesdesigns. Standards that hold because they are useful, not because they are mandated.
Run the platform well.Own service levels, reliability, security posture, and unit economics. Know the numbers before you are asked for them.
Partner across the portfolio.Work directly with product engineering leaders, architecture, data engineering, SRE, and security to keep the platform aligned with where the business is going.
Build the team.Hire well, mentor directly, and set the technical standard by example.
Required qualifications
8+yearsbuilding and operating production software, including 3+ years leading engineering teams (managing engineers and/or managers).
Demonstrably hands-on. You can read the code, run the system, debug a production issue, and lead a design review with authority.
Strong distributed systems and platform architecture background, including API design, service-to-service authentication, and multi-tenant data isolation.
Deep working knowledge ofat least twoof the following, and credible working knowledge of the rest:
Analytics and BI platforms, distributed SQL query engines, and embedded analytics delivery
LLM application engineering agent frameworks, retrieval-augmented generation, vector search, evaluation, and cost management
Workflow and orchestration platforms and their operational characteristics
Modern web application platforms and front-end architecture at scale
Production experience with AWS, Kubernetes, infrastructure as code, andGitOps-based continuous delivery.
Practical identity and access experience: OIDC/OAuth2, enterprise IdP integration, and token-based authorization patterns.
A track recordof taking an existing platform and materially improving its architecture, reliability, or adoption with specifics you can walk us through.
Preferred qualifications
Experience running an internal platform consumed by multiple product teams, including adoption strategy and platform-vs-product boundary decisions.
Experience shipping AI capabilities into B2B SaaS products with real customers, real data governance requirements, andreal costconstraints.
Experience in a multi-product portfolio where standardizationhas tobe earned across teams rather than mandated.
B2B SaaS at scale; fuel, convenience retail,logistics, or payments domain exposure is a plus.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.