Project Delivery Manager
- Role
- Project Management
- Experience
- Senior
- Employment
- Full-time
Open to EG, JO, LB only. Set where you work from to check your eligibility.
No BS summary
Project/Delivery Manager with 5–8 years in SaaS implementation, technical project management, or digital/platform delivery. Needs 3+ years delivering enterprise projects with business and IT stakeholders, plus integrations, APIs, data-driven workflows, and Agile/Scrum experience. CX, contact centers, CRM, or customer-facing platforms are a strong plus.
Core skills
Required skills
Optional skills
About Lucidya Lucidya is building the next generation of AI-powered customer experience solutions for enterprises across the MENA region. Our new AI Agents business line focuses on deploying intelligent, enterprise-grade AI agents that automate, assist, and augment customer-facing and operational workflows - securely, reliably, and at scale. This role sits at the heart of turning AI agent concepts into live, business-impacting solutions. About the Role The Project / Delivery Manager owns one critical question: “How do we execute what we promised?” You take the Solution Consultant’s vision and turn it into a clear execution plan, structured backlog, and predictable delivery rhythm - from initial scoping through go-live and stabilization. You are the operational backbone of AI agent pilots and enterprise deployments, ensuring alignment across clients, engineering, data, and AI teams while keeping delivery on track. Key Responsibilities 1. Scoping & Handover from Solution Consultant You step in once a pilot or project is conceptually approved. Formal Handover Receive full delivery context, including: Discovery findings Workflow maps and agent logic Success criteria and KPIs Pilot narrative and client expectations Clarify: Scope, constraints, dependencies, and assumptions Technical and operational boundaries Scope Confirmation Translate high-level workflows into clear delivery components: AI Agent versions (v0, v1, v2…) Integrations, channels, and data sources Dashboards, reporting, and monitoring Training, enablement, and documentation Align internally and with the client on: What is in scope vs out of scope for each phase 2. Detailed Planning & Backlog Management This is where ideas become execution. You own: Building the delivery plan and timeline: Milestones, sprints, and go-live checkpoints Cross-team dependencies (AI, backend, integrations, data, CX ops) Creating and maintaining the delivery backlog: Break down deliverables into tasks and subtasks Assign clear owners (AI Agent Engineers, Backend, Frontend, Data, Solutions) Keeping tools accurate and trusted: Trello / Jira / Notion as the single source of truth Task status, blockers, due dates, and changes 3. Coordination & Day-to-Day Execution You are the operational heartbeat of each pilot or project. Responsibilities include: Running regular execution cadences: Standups and check-ins Progress reviews and decision syncs Ensuring tight collaboration between: Solution Consultants (business & workflows) Engineering and AI teams (implementation) Client stakeholders (CX, IT, Operations, Compliance) Driving execution discipline: Clear meeting notes Action items with owners and deadlines Relentless follow-up until closure 4. Risk, Change & Stakeholder Management AI agent delivery comes with moving parts - you own visibility and control. You will: Maintain a risk & issues log covering: Technical risks (data access, integrations, latency, environments) Business risks (scope creep, stakeholder shifts, external dependencies) Manage change transparently: Assess impact on scope, timelines, and delivery Align with stakeholders before execution Provide clear, consistent communication: Status updates Escalations when needed Expectation management throughout the lifecycle 5. UAT, Go-Live & Post-Go-Live Stabilization Plan and coordinate: UAT cycles and acceptance criteria Go-live readiness and rollout plans Ensure smooth transition: Monitor early performance and issues Coordinate fixes and optimizations Own final handover: Documentation Support transition Clear ownership post-delivery Requirements 5-8 years in: SaaS implementation Technical project management Digital or platform delivery 3+ years delivering enterprise projects with multiple stakeholders (business & IT) Proven experience with: Integrations, APIs, and data-driven workflows Background in CX, contact centers, CRM, or customer-facing platforms is a strong plus Experience working closely with product and engineering teams in Agile/Scrum environments Must-Have Skills Project & Delivery Excellence Strong command of: Scoping, timelines, milestones RAID (Risks, Assumptions, Issues, Dependencies) Confident running: Standups, execution reviews, steering meetings Technical Literacy (Non-Coding) Comfortable with: API-based integrations and webhooks Data flows between systems Able to: Read basic API documentation and JSON payloads Translate technical constraints into delivery decisions Solid conceptual understanding of: SaaS platforms LLMs and AI agent workflows Stakeholder Management & Communication Can confidently manage: CX leadership IT and engineering teams Internal product and AI stakeholders Produces: Clear documentation Actionable recaps Concise, honest status updates Execution Mindset Turns ideas into: Tasks, owners, and deadlines Keeps delivery tools always current and reliable Strong sense of ownership and follow-through AI Project Awareness Comfortable with: Iterative AI delivery (experiments, versions, evaluation cycles) Data privacy, guardrails, and quality metrics Understands that AI delivery is adaptive, not linear Why Join Lucidya’s AI Agents Team Work at the intersection of AI, CX, and enterprise delivery Shape how AI agents are deployed in real-world, high-impact environments Partner with strong product, AI, and engineering teams Own delivery end-to-end - not just coordination Help define delivery standards for a brand-new AI business line Apply Now and help us redefine the future of Customer Experience with AI Agents.
What you'll do
- Own execution planning for AI agent pilots and enterprise deployments from initial scoping through go-live and stabilization.
- Receive full delivery context after a pilot or project is conceptually approved, including discovery findings, workflow maps and agent logic, success criteria and KPIs, pilot narrative, and client expectations.
- Clarify scope, constraints, dependencies, assumptions, and technical and operational boundaries.
- Translate high-level workflows into clear delivery components, including AI Agent versions, integrations, channels, data sources, dashboards, reporting, monitoring, training, enablement, and documentation.
- Align internally and with the client on what is in scope versus out of scope for each phase.
- Build the delivery plan and timeline, including milestones, sprints, go-live checkpoints, and cross-team dependencies across AI, backend, integrations, data, and CX ops.
- Create and maintain the delivery backlog.
- Break down deliverables into tasks and subtasks.
- Assign clear owners across AI Agent Engineers, Backend, Frontend, Data, and Solutions.
- Keep Trello, Jira, or Notion accurate and trusted as the single source of truth.
- Maintain task status, blockers, due dates, and changes.
- Run regular execution cadences, including standups, check-ins, progress reviews, and decision syncs.
- Ensure tight collaboration between Solution Consultants, engineering and AI teams, and client stakeholders across CX, IT, Operations, and Compliance.
- Drive execution discipline through clear meeting notes, action items with owners and deadlines, and follow-up until closure.
- Maintain a risk and issues log covering technical risks such as data access, integrations, latency, and environments, and business risks such as scope creep, stakeholder shifts, and external dependencies.
- Manage change transparently by assessing impact on scope, timelines, and delivery.
- Align with stakeholders before execution.
- Provide clear, consistent communication, including status updates, escalations when needed, and expectation management throughout the lifecycle.
- Plan and coordinate UAT cycles and acceptance criteria.
- Plan and coordinate go-live readiness and rollout plans.
- Monitor early performance and issues after go-live.
- Coordinate fixes and optimizations.
- Own final handover, including documentation, support transition, and clear ownership post-delivery.
What they require
- 5-8 years in SaaS implementation, technical project management, digital or platform delivery.
- 3+ years delivering enterprise projects with multiple stakeholders (business & IT).
- Proven experience with integrations, APIs, and data-driven workflows.
- Preferred: Background in CX, contact centers, CRM, or customer-facing platforms is a strong plus.
- Experience working closely with product and engineering teams in Agile/Scrum environments.
- Strong command of scoping, timelines, milestones, and RAID (Risks, Assumptions, Issues, Dependencies).
- Confident running standups, execution reviews, and steering meetings.
- Comfortable with API-based integrations and webhooks.
- Comfortable with data flows between systems.
- Able to read basic API documentation and JSON payloads.
- Able to translate technical constraints into delivery decisions.
- Solid conceptual understanding of SaaS platforms.
- Solid conceptual understanding of LLMs and AI agent workflows.
- Can confidently manage CX leadership, IT and engineering teams, and internal product and AI stakeholders.
- Produces clear documentation, actionable recaps, and concise, honest status updates.
- Turns ideas into tasks, owners, and deadlines.
- Keeps delivery tools always current and reliable.
- Strong sense of ownership and follow-through.
- Comfortable with iterative AI delivery, including experiments, versions, and evaluation cycles.
- Comfortable with data privacy, guardrails, and quality metrics.
- Understands that AI delivery is adaptive, not linear.
Benefits
- Work at the intersection of AI, CX, and enterprise delivery.
- Shape how AI agents are deployed in real-world, high-impact environments.
- Partner with strong product, AI, and engineering teams.
- Own delivery end-to-end - not just coordination.
- Help define delivery standards for a brand-new AI business line.
Lucidya is an AI-native platform for customer experience (CX) intelligence that helps organizations understand their customers and take action across the entire customer lifecycle. Our platform brings together products including Social Listening, OmniServe, Survey, and AI Agent, helping enterprise organizations across the region turn customer data into better experiences and measurable business outcomes.