Project Manager, Data Analyst, IT Project Manager

Job Role

A dedicated startup is being formed to industrialize and scale a secure, AI-enabled, multi-source decision-support software offering. The platform is a multi-sensor fusion and agentic AI solution connecting to diverse data sources (for example geospatial layers, imagery, video, and other operational signals). This role will support the delivery of a scalable product and contribute to establishing the processes, standards, and collaboration practices required for sustainable growth.

Own end-to-end delivery of platform and product initiatives spanning software engineering, geospatial workflows, LLM-enabled capabilities, and agentic orchestration. Drive execution, governance, risk management, and stakeholder alignment from discovery to release.

• Define scope, outcomes, success metrics, and release plans (MVP to iterations)
• Build and maintain integrated delivery plans: milestones, dependencies, resourcing, and critical path
• Run agile delivery cadence: planning, standups, reviews, retros, and roadmap alignment
• Own RAID (Risks, Assumptions, Issues, Decisions), change control, and escalations
• Coordinate cross-functional streams: platform, data and GIS, ML and LLM, UI and visualization, Dev Ops and MLOps
• Align stakeholders on priorities, sequencing, and trade-offs; keep delivery predictable and transparent
• Coordinate external partners and vendors (APIs, SDKs, data sources, model contributors)
• Support PR and PO follow-up where needed to unblock delivery (with procurement and finance)
• Support contract and SOW coordination: consolidate inputs, manage versions, route for review with Legal and Procurement
• Support recruiting: role prioritization inputs, interview loop coordination support, onboarding readiness
• Operate in startup mode: execution-first, flexible, able to pivot while keeping control of priorities
• te cross-functional streams: platform, data and GIS, ML and LLM, UI and visualization, Dev Ops and MLOps

• 5+ years managing software and AI programs in a product environment
• Experience with agile delivery (Scrum or Kanban)
• PMP/PRINCE2/Scrum certification is a plus
• Tools (examples)
• Jira/Linear and Confluence/Notion
• Git Hub/Git Lab and CI/CD dashboards
• Miro and Power BI (optional)
• KPIs
  • Release predictability and milestone adherence
  • Risk closure rate and reduction of delivery blockers
  • Cycle time and throughput (team-level)
  • Quality leakage (defects after release)
  • Stakeholder satisfaction