Sr. Technical Program Manager, Geo-Graph
Amazon
DESCRIPTION
## Who Are We?
The North Star vision of the Geospatial organization is to optimize logistics operations for Amazon Deliveries by empowering every person performing pickup or delivery services, independent of tenure, affinity, payload, mode of transport, or geography, to deliver a best-in-class customer experience using logistics-centric geospatial data, intelligence, and experiences. To achieve this vision, with optimal quality, speed, and cost, requires innovation in a high-fidelity virtual model of the real-world, precise solvers that that operate over that model to enable safe and efficient journey planning, and intuitive travel, destination, and chronicling experiences that enable successful journeys.
The Geo-Graph team within Geospatial owns (i) the foundational big data AI/ML systems that enable the learning and curation of safe and efficient digital maps data for Amazon Delivery logistics, (ii) the transporter facing visual map experiences and related feedback gathering and processing, and (iii) close looping on geospatial data defects with map editing tools that power manual data operations where AI/ML falls short. The organization builds bigdata pipelines powered by AI/ML models that curate raw maps data from multiple heterogenous sources and transform them into data artifacts consumed in (i) planning of delivery routes, (ii) providing turn-by-turn navigation instructions, (iii) displaying the visual map tile for transporters, (iv) generating safety alerts (such as speeding, road incidents), and (v) defining jurisdictions of delivery stations. These AI/ML pipelines are augmented with the geospatial data quality flywheel from (i) the transporter feedback experience for submitting high quality actionable feedback on delivery defects, (ii) map-editor experience for actioning on transporter reported defects, and (iii) the systems that power that manual data operation for close looping on this feedback.
## Why build another Mapping system?
The answer is simple, we want to invent and simplify the way our partners, customers, and teams utilize this mapping system. We want to dive deep into the complex obstructions and enable more in-depth solutions. We will utilize multiple modes of transportation, and traffic cognizance to optimize and simplify the ability to reach millions of delivery points around the world. As Amazon, we are uniquely positioned to understand the mapping needs of delivery drivers during their on-road and at-stop navigation experiences and leverage AI/ML to generate unique insights from these rich dataset to build a logistics centric mapping experience that excels in all the aspects of coverage, accuracy, freshness and richness over consumer grade maps in the industry.
Key job responsibilities
This Sr. TPM role is responsible for managing the lifecycle of complex geospatial AI/ML projects aimed at improving the coverage, quality, richness and freshness of maps data that result in considerable impact to route planning efficiency, navigation experience and driver safety. The Sr. TPM is accountable for the overall technical strategy on how map data improvements can be leveraged by cross-organizational teams for developing driver facing map features and contributes to its operational planning. The Sr. TPM should be well versed with the limitations, scaling factors, boundary conditions, and reasons behind architectural decisions for different geospatial system. The Sr. TPM closely partners with Sr. SDEs and influences architectural decisions by providing business context and long-term program perspective. The Sr. TPM leads programs that often require cross-functional collaboration with maps product managers, LMAQ map editing program managers, geospatial scientists and station operations across multiple geographies. The role requires the Sr. TPM to drive crisp data-driven decisions across these stakeholders and leaders (Directors, VPs) by providing them context to technical system abilities and architectural limitations. Additionally, the Sr. TPM is expected to partner with product managers in framing and executing data contracts with external 3P data providers. This may involve technical discussions directly with tech leads of these 3P companies to arrive at a consensus on the technical terms (like APIs and SLAs) of the data contract.