About the role
The candidate will have responsibilities across the following functions:
Own the architecture of the money path:
- Design a demand-source-agnostic serving layer: any exchange, ad server or deal plugs in behind one contract we own (OpenRTB 2.6 with Glance extensions).
- Keep decisioning — auction, floors, priority and ad-load policy — in our platform, never in adapters or partner consoles.
- Define the rendering contract the client SDK depends on (native, VAST, MRAID/HTML).
- Make the big calls and write them down: ADRs, latency budgets, build-versus-use decisions with InMobi platform teams.
Serve ads inside the Glance experience:
- Build ad slots into Glance's content feed, with ad load balanced against dismiss rate, session depth and retention.
- Design for prefetch: ads fetched ahead of time and shown later, sometimes offline - caching, expiry, pacing and delayed impression beacons all have to hold.
- Own per-user frequency and ad load across every demand source, within latency, battery and memory budgets on low-end Android.
Set the bar and grow the team:
- Run design reviews across serving, SDK, automation and revenue data, and own the API contracts between them.
- Make "what proves this? " the first question on any pricing or serving change, AI-assisted code included: replay evals, invariant checks, auto-rollback canaries.
- Be accountable for integrity gates: creative safety, invalid traffic, policy compliance.
- Review revenue-event and partner-reconciliation design so the numbers hold up to OEM audit.
- Mentor senior engineers into area leads, and make sure every service has a second owner
Requirements:
- 10+ years, including ownership of a low-latency, high-throughput system where a bad deploy shows up as lost revenue - ad serving, payments, trading or pricing.
- Distributed systems depth: partitioning, replication, consistency, failure modes, graceful degradation.
- Deep, hands-on Java and Spring Boot (our serving stack), including JVM/GC tuning for low latency; comfortable in Python (FastAPI) for ML and data services.
- Cloud (GCP or AWS), Kubernetes and CI/CD, designing for cost of serving, not just uptime.
- Event pipelines at scale (Kafka, Spark or Flink), reconciled against an external source of truth.
- Safe releases without a manual pass: contract and replay testing, canaries, automated rollback, SL Os; you've been paged on RFCs and ADRs that lead to decisions, and influence across teams you don't manage.
Nice to have
- Sell-side ad tech: SSPs, ad servers, Prebid / Prebid Server, Google Ad Manager.
- OpenRTB, VAST, MRAID and OM SDK; privacy signals (T CF, GPP) and supply-chain transparency (schain, sellers.json, app-ads. txt).
- Android or mobile SDK work under size, battery and cold-start budgets.
- Consent frameworks (DPDP, GDPR, LGPD), invalid-traffic defences, or partner-billing systems that external partners audit.