Program Manager: Geospatial Data & AI Platform

Program Manager: Geospatial Data & AI Platform (Highways / Infrastructure) About the Role We are seeking a Program Manager to lead the delivery of a large-scale, cloud-native geospatial analytics platform that ingests, processes, and analyzes road-condition and dashcam data at national production scale. The platform combines full-stack applications, GIS processing, computer-vision/ML models for road-defect detection, and a Databricks- based lakehouse. The ideal candidate pairs strong program management discipline with genuine technical uency across application, cloud infrastructure, data engineering, and applied ML. Key Responsibilities Application Development & GIS ¢ Lead delivery of full-stack applications (JavaScript/React front end; containerized backend APIs and worker services) for defect reporting, GIS visualization, and analytics dashboards Oversee API design and delivery across REST/HTTP APIs (API Gateway), event-driven ingestion (Lambda, SQS, EventBridge), and caching/search layers (Redis/ElastiCache, OpenSearch) Coordinate GIS processing workstreams and map-based frontend delivery via CDN (CloudFront) Cloud Infrastructure (AWS) ¢ Own infrastructure provisioning across environments in AWS (ap-south-1 / Mumbai), including ECS-on-EC2 compute, Aurora PostgreSQL (Multi-AZ), DynamoDB, VPC networking (NAT, VPC endpoints, ALB), and bastion/admin access ¢ Drive environment separation, tagging, and shared-vs-dedicated service strategy across production and staging (common Databricks/governance layers vs. environment-isolated data and namespaces) ¢ ¢ Govern security, encryption, and compliance baselines: KMS/CMKs, Secrets Manager, GuardDuty, AWS Cong, AWS Backup, Route 53/ACM Manage cost, capacity, and scaling decisions (e.g., autoscaling compute, lifecycle policies to S3-IA/Glacier for petabyte-scale raw archive) Data Engineering & Warehouse (Databricks + AWS) ¢ ¢ ¢ ¢ Lead the lakehouse build-out on Databricks (SQL/Jobs/Photon compute, Workows orchestration) with a node-scaling model tied to data volume growth Oversee ETL/ingestion pipelines (AWS Glue, optional MWAA/Airow) and ad-hoc analytics on the S3 data lake (Athena, Parquet/ORC) Establish data governance and lineage across Lake Formation and Databricks Unity Catalog, with separate catalogs/schemas per environment Manage the evaluation of a curated warehouse path (Redshift Serverless/RA3) alongside or instead of Databricks Data Science & AI/ML ¢ ¢ ¢ Manage development and deployment of computer-vision and predictive models for road-defect scoring and dashcam analytics (SageMaker real-time and batch inference; GPU training on EC2 g4dn / SageMaker p3) Oversee the model validation pipeline, including SageMaker Ground Truth labeling workows (auto-label + human audit) across multi-vendor dashcam eets the platform's largest cost driver, requiring tight scope, sampling, and budget control Coordinate descriptive-analytics and algorithm work (e.g., deduplication and coverage-gap analysis) Required Qualications ¢ ¢ ¢ ¢ ¢ ¢ 8+ years of program/project management in technology-driven, data-intensive environments Proven delivery of full-stack applications (JavaScript, React, containerized backends) Hands-on experience provisioning and governing AWS infrastructure (EC2/ECS, RDS/Aurora, VPC networking, IAM/KMS, S3 at scale) Experience overseeing AI/ML model development and deployment, ideally computer vision, on SageMaker or equivalent Experience with lakehouse/data-warehouse platforms, specically Databricks (and familiarity with Redshift, Glue, Athena) Demonstrated ability to manage multi-environment delivery with cost, security, and governance discipline ¢ Strong stakeholder management and cross-functional leadership; Agile/Scrum familiarity Stakeholder & Team Management ¢ Coordinate delivery across the application team (front-end, backend), data engineering team (lakehouse, ETL, warehouse), and data science team (CV/predictive modeling), sequencing cross-team dependencies so pipelines and labeled data are ready when models need them, and model outputs/APIs are production-ready when the app team integrates them ¢ ¢ Manage upward and outward to client and public-sector sponsors (e.g., client/program leadership), infrastructure and security/compliance reviewers, and external vendors (dashcam eet and labeling providers) Translate technical trade-os into clear scope, cost, and timeline decisions, maintaining a shared view of progress, risks, and priorities across all parties Preferred Qualications ¢ ¢ ¢ ¢ ¢ Bachelor's/Master's in Computer Science, Engineering, Data Science, or GIS PMP, CSM, or AWS certication (e.g., Solutions Architect) Prior hands-on background as a developer, data engineer, or data scientist Experience with geospatial/GIS platforms or public-sector / infrastructure programs Experience managing large data-volume programs (multi-petabyte) and associated cloud cost optimization ¢ Vendor and budget management across managed-labeling or eld-data-collection eets What You'll Bring ¢ ¢ ¢ Fluency translating across application, cloud, data-engineering, and ML teams Comfort operating from front-end through petabyte-scale data and applied ML A delivery and cost-focused mindset with strong risk management, especially where a single workstream (e.g., ML validation/labeling) dominates program spend