About the team.
InMobis DSP is a real-time bidding platform operating at millions of queries per second with sub-50ms latency SLAs, built on a Scala, Pekko, gRPC, and GKE stack. The organization spans ~60 people across engineering and applied science, and is in the middle of a significant platform re-architecture toward a commerce-first, ML-driven model including a modernized feature store and lakehouse layer, and a growing applied science presence across multiple geographies focused on commerce advertising. This role sits within InMobis central TPM organization (which reports to the Group CTO) and works in close, day-to-day partnership with the Head of Technology for DSP and their leadership team (Director of Engineering, Director of Applied Science, Principal Scientist).
What youll own.
- End-to-end program management across DSPs full portfolio, spanning platform/infra re-architecture, applied science/ML initiatives, and customer/commerce-facing feature launches. Youre the connective tissue across all three, not siloed into one.
- Cross geo co-ordination across Bangalore, Beijing, and Lucknow, as the applied science and engineering org scales, aligning roadmaps, resolving dependencies, and keeping distributed teams working off a shared plan despite time zone and org-distance challenges.
- Translating strategy into execution, partnering with DSPs engineering and applied science leadership to break down large initiatives (e.g., feature store migration, new bidding/commerce capabilities) into sequenced, resourced, trackable plans.
- Program governance, roadmaps, dependency maps, RAID logs, milestone tracking, and operating cadences (planning cycles, status reviews, exec updates) suited to a real-time, high-QPS distributed systems environment.
- Risk identification and mitigation across technically complex, cross-team efforts surfacing conflicts early, before they hit sub-50ms latency SLAs or launch timelines.
- Representing DSP programs upward and outward, reporting into the central TPM org and Group CTO leadership, while remaining deeply embedded in DSPs day-to-day technical context.
- Stakeholder alignment across engineering, applied science, and adjacent partner teams (data platform, commerce/monetization, infra).
Who you are.
- 3-6 years of technical program management experience, ideally within ad-tech, real-time bidding, or large-scale distributed/low-latency systems.
- Proven experience running programs that span both software engineering and applied science/ML teams, comfortable with the different cadences and artifacts each discipline needs.
- Working technical fluency with distributed systems concepts (gRPC, streaming/Kafka, Kubernetes/GKE, service mesh), enough to engage credibly with senior engineers and scientists, not just track Jira tickets.
- Working understanding of the applied science/ML project lifecycle, experimentation design, offline vs. online metrics, feature engineering, model evaluation, and rollout/A-B testing, sufficient to plan, sequence, and de-risk applied science programs rather than treat them as black boxes.
- Experience coordinating across geographies and time zones (India-China or similar), including navigating cultural and organizational distance across multiple sites.
- Strong executive communication and stakeholder management skills, able to operate comfortably with Group CTO-level stakeholders as well as ICs.
- A track record of building lightweight but effective program operating rhythms in fastmoving, technically deep orgs, not heavyweight process for its own sake.
- Bachelors/Masters in Computer Science, Engineering, or a related technical field preferred