Technical Project Manager / Business Analyst (AI & Data Delivery)

We are looking for an experienced, hands-on Technical Project Manager / Business Analyst who can take ownership of both upstream business discovery and day-to-day technical delivery across the company’s client engagements. You will work directly with business stakeholders to map existing and desired workflows, clarify problems and requirements, and turn them into actionable AI and automation use cases for engineering evaluation. Working closely with our CEO and senior engineers, you will also keep delivery plans, decisions, dependencies, client communications and follow-through on track. This is not a purely administrative coordinator or high-level PMO reporting role. We need someone who can move confidently between business stakeholders and engineers: understand enterprise systems and data flows, ask informed technical questions, identify dependencies and risks, and translate discussions into clear decisions and actions. The role also involves maintaining project plans, preparing client-facing updates and presentations, and independently driving stakeholder follow-up. You do not need to write production code or own solution architecture.

Examples of the work you may support

* Enterprise construction program: Coordinate several parallel AI, data and automation workstreams involving executive reporting, ERP/project-system integrations, operational workflows and vendor coordination. Prepare daily/weekly updates, maintain delivery and use-case boards, and keep decisions and owners visible. * Internal AI enablement: Support an engineering company in organizing its internal AI team, maintaining its initiative roadmap and backlog, coordinating technical review sessions and tracking progress alongside the company’s technical leads. * AI portfolio and roadmaps: Help an infrastructure organization understand workflows and business pain points, organize and prioritize AI opportunities across functions, facilitate discovery sessions, capture current- and future-state processes, and translate selected priorities into clear roadmaps and presentations.

* Lead process and SOP discovery: Work directly with business stakeholders to understand current operations, pain points, systems, handoffs and exceptions. Map existing (as-is) and desired (to-be) workflows and identify gaps and opportunities for improvement. * Define actionable AI use cases: Translate business problems and workflow findings into clear use-case briefs for engineering evaluation, documenting users, desired outcomes, proposed workflows, available data, dependencies and success measures. Collaborate with technical leads on feasibility and consider simpler non-AI solutions where appropriate. * Own delivery tracking: Maintain accurate project boards and action logs (primarily monday.com) across development activities, use-case portfolios and client requests. Track status, owners, next steps, deadlines, blockers, decisions and dependencies. * Produce client-ready updates: Consolidate developer updates, meeting notes and communications from Slack, Microsoft Teams, email and project boards into concise daily updates, weekly summaries and executive progress reports. Verify facts and flag conflicting or missing information. * Drive follow-through: Prepare agendas, capture decisions and action items, coordinate meetings, obtain missing inputs, follow up with internal and client stakeholders, and make sure commitments are closed out. * Draft clear communications: Prepare thoughtful emails, meeting invitations, follow-ups and issue summaries for business and technical stakeholders; adapt the level of detail and tone to the audience. * Develop project materials: Help build and maintain presentations, status briefs, implementation plans, process/workflow documentation, SOPs and client-ready deliverables, using existing materials and agreed decisions rather than starting from scratch. * Support planning and prioritization: Organize use-case inventories, requirements, priorities, milestones and roadmaps; work with technical leads to capture assumptions, feasibility considerations and implementation dependencies. * Coordinate across teams: Work with the company’s engineers and client-side operations, finance, IT, innovation and vendor contacts to clarify ownership, prerequisites, handoffs and timelines. * Keep delivery risks visible: Identify emerging delays, unclear scope, unanswered questions, stale project data and changes that could affect effort or commitments. Escalate what requires the CEO’s or technical lead’s judgment. * Use tools thoughtfully: Apply AI-assisted research, drafting and synthesis where appropriate, while checking sources, protecting confidential information and ensuring every client-facing statement is accurate.