À propos de ce poste Sr. Manager, Engineering chez Pditechnologies
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 time in architecture, 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.
What you'll own
|
Domain |
Scope |
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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 platform provides |
|
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 |
What you'll do
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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.
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Treat the platform as a product. Define what it offers, who consumes it, and where the boundary sits between platform and product. Make adoption a documented, repeatable path rather than a bespoke project each time.
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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.
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Raise the engineering bar on delivery. Automated, safe, observable releases. Design review that improves designs. Standards that hold because they are useful, not because they are mandated.
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Run the platform well. Own service levels, reliability, security posture, and unit economics. Know the numbers before you are asked for them.
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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.
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Build the team. Hire well, mentor directly, and set the technical standard by example.
Required qualifications
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8+ years building and operating production software, including 3+ years leading engineering teams (managing engineers and/or managers).
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Demonstrably hands-on. You can read the code, run the system, debug a production issue, and lead a design review with authority.
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Strong distributed systems and platform architecture background, including API design, service-to-service authentication, and multi-tenant data isolation.
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Deep working knowledge of at least two of the following, and credible working knowledge of the rest:
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Analytics and BI platforms, distributed SQL query engines, and embedded analytics delivery
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LLM application engineering — agent frameworks, retrieval-augmented generation, vector search, evaluation, and cost management
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Workflow and orchestration platforms and their operational characteristics
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Modern web application platforms and front-end architecture at scale
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Production experience with AWS, Kubernetes, infrastructure as code, and GitOps-based continuous delivery.
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Practical identity and access experience: OIDC/OAuth2, enterprise IdP integration, and token-based authorization patterns.
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A track record of taking an existing platform and materially improving its architecture, reliability, or adoption — with specifics you can walk us through.
Preferred qualifications
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Experience running an internal platform consumed by multiple product teams, including adoption strategy and platform-vs-product boundary decisions.
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Experience shipping AI capabilities into B2B SaaS products with real customers, real data governance requirements, and real cost constraints.
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Experience in a multi-product portfolio where standardization has to be earned across teams rather than mandated.
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B2B SaaS at scale; fuel, convenience retail, logistics, or payments domain exposure is a plus.
