Jobs at Metropolis Technologies

Leads the internal Applied AI product roadmap, translating operational challenges into AI applications, RAG implementations, agentic workflows, and automation systems. Partners with Finance, Operations, and go-to-market leaders to identify opportunities, define requirements and success metrics, collaborate with engineers and vendors, prototype solutions, drive adoption, and measure business impact. The role also oversees agile development, change management, reliability, and continuous improvement of internal AI tools.

Leads data science for growth marketing by building attribution, lifetime value, acquisition cost, retention, and predictive models. Designs A/B tests, geo-experiments, holdout tests, and incrementality studies to optimize marketing budgets and unit economics. Partners with Growth, Product, Finance, analytics, and engineering teams on data pipelines, event tracking, dashboards, and strategic decision-making. Applies causal inference, advanced analytics, and AI tools to drive user acquisition, retention, and profitable growth.

Leads engineering operations and strategy across a high-growth organization. Owns shared engineering processes, a $50M–$100M+ budget, vendor forecasting and relationships, strategic decisions, M&A technology due diligence, migrations, and cross-functional alignment. Partners with executives to resolve complex operational challenges, translate business goals into execution plans, and improve technology operations using AI tools and formal methodologies.

Own the architecture and technical direction of a high-volume recognition platform spanning edge ingestion, identity resolution, real-time decisioning, notifications, and operator tools. Lead streaming pipeline design, privacy and consent models, observability, reliability, testing, progressive delivery, RFCs, cross-functional alignment, and mentorship. Build systems that combine deterministic rules with probabilistic computer vision signals under physical-world deployment constraints.

Own the vision, strategy, and roadmap for payment processing, subscription billing, enterprise reporting, and revenue reconciliation. Manage payment processor relationships, define financial and operational metrics, partner with Engineering and Finance, communicate with executives and clients, and eventually build a product management team. The role requires deep payments expertise, technical and data literacy, strong stakeholder management, and experience driving clarity in complex environments.

Design and build foundational web services, service mesh infrastructure, developer tooling, CI/CD automation, and highly reliable distributed systems. Architect scalable APIs and data consistency patterns, optimize high-throughput systems, establish observability and reliability practices, and mentor engineers. The role supports millions of transactions across mobility products and requires collaboration across application, infrastructure, and advanced technology teams.

Design and lead backend services for Metropolis’s incentive and rewards platform. Build real-time event-driven systems, compliance and preference services, personalized decisioning frameworks, identity systems, attribution tools, and scalable eligibility and partner configuration services. Collaborate with Product, Marketing, and Data on the technical roadmap, mentor engineers, lead technical discussions, and manage the full software development lifecycle through production deployment.

Build and own scalable full-stack mobility platform features across databases, backend APIs, and user interfaces. Collaborate with UX, product, and engineering teams to deliver high-quality experiences for high-throughput environments. Lead projects from inception through production, improve performance and reliability, champion engineering best practices, mentor junior engineers, and evaluate tools and frameworks for continuous platform improvement.

Leads retail growth and commercial strategy, owning the segment growth target, national-account wins, partnerships, B2B marketing, product-market alignment, and vertical expansion. Develops value propositions, deal structures, product roadmaps, reporting frameworks, industry partnerships, thought leadership, and cross-functional execution across sales, product, marketing, operations, and data teams.

Leads hospitality-sector growth strategy, commercial expansion, national account sales, partnerships, vertical marketing, and product commercialization. Owns the segment growth target and collaborates with sales, operations, marketing, product, and data teams to develop value propositions, deal structures, roadmaps, dashboards, and market positioning. The role requires extensive hospitality industry relationships, financial modeling, P&L management, enterprise business development, and cross-functional leadership.

Own platform-wide reliability engineering for 99.9%+ uptime. Design failover, multi-region deployments, database replication, disaster recovery, observability, synthetic monitoring, SLO alerting, incident management, chaos engineering, and resilience patterns. Build dependency mirrors and automation while influencing architecture and establishing reliability standards across teams. The role requires expertise in distributed systems, AWS, databases, Datadog, JVM performance, Java or Scala, and production operations at scale.

Drive corporate financial forecasting, variance analysis, financial modeling, capital allocation, long-range planning, ROI analysis, and OpEx/headcount management. Advise business units, prepare board reporting and dashboards, validate financial data, improve workflows, automate reporting, shorten month-end cycles, and document finance procedures. The role requires strong Excel, ERP/EPM, GAAP, financial analysis, generative AI, data synthesis, executive communication, and multitasking skills.

The Senior AI Engineer will design and build AI-powered automation tools, maintain LLM systems, and collaborate with business analysts to enhance processes across various operations.

As a Senior Machine Learning Engineer, you will design and deploy computer vision models, collaborate with teams, and mentor juniors while ensuring high-performance solutions.

Design, develop, and maintain scalable backend services in Java and Scala; implement gRPC APIs; use Redis, MySQL/PostgreSQL and Kafka for low-latency data and event streaming; deploy and manage microservices on Kubernetes; collaborate with Hardware, ML, and Operations teams; diagnose and resolve performance and scalability issues.

Lead application and product security across web, mobile, API, AI/CV, and cloud-native systems. Drive secure SDLC, DevSecOps, CI/CD and supply chain security, threat modeling, tooling/automation, vulnerability remediation, and developer enablement while partnering closely with engineering teams.

Senior Cloud Infrastructure Engineer responsible for designing, building, and operating central cloud infrastructure on AWS; managing observability (Datadog), version control and CI/CD (Git/GitHub); and collaborating closely with product and engineering teams. Role requires regular on-site presence (four days/week) and contributes to platform reliability and scalability.

Leads complex recognition technology deployments from planning through go-live, serving as the technical design and project management owner. Responsibilities include developing project plans, managing budgets, schedules, risks, integrators, customers, site audits, technical architectures, quality gates, and support handoffs. The role also improves deployment processes, translates customer requirements into scalable designs, and supports regional business development.