Overview
Delivery Manager — SaaS Cloud Application (R&D). Reports to: VP, Research & Development. Type: Full-time.
We’re seeking a hands-on Technical Delivery Manager to drive the end-to-end delivery of a modern SaaS cloud application. You will translate the product roadmap into actionable plans for engineering, run the day-to-day execution (Scrum / Kanban), remove blockers quickly, and ship high-quality releases on schedule. You’re comfortable discussing technologies like Unity3D builds, Heygen, TypeScript / modern web stacks, and AWS architectures—and you champion pragmatic use of AI-assisted development to accelerate delivery while maintaining quality.
What You’ll Own (Key Outcomes)
- On-time, high-quality releases: Hit committed release dates with clear exit / entry criteria and a controlled rollout plan.
- Roadmap → reality: Decompose roadmap items into epics, user stories, tasks, and acceptance criteria with crisp definitions of done.
- Flow efficiency: Identify and eliminate waste (handoffs, queues, rework) to improve lead time and predictability.
- Signal-rich reporting: Provide the VP of R&D with concise daily status (plan, progress, risks, decisions needed) and weekly rollups.
- AI-enabled productivity: Increase team velocity by responsibly adopting AI tools while safeguarding security and code quality.
Responsibilities
- Delivery Leadership
- Own the delivery plan: scope, milestones, dependencies, and critical path across backend, web, and overall delivery.
- Run daily Scrum, sprint planning, reviews, and retros. Keep teams unblocked and laser-focused on priorities.
- Maintain a healthy, prioritized backlog; ensure stories have clear acceptance criteria and testability.
- Track and drive against KPIs (lead time, cycle time, throughput, sprint predictability, escape rate, deployment frequency).
- Technical Program Execution
- Collaborate with Tech Leads to break work into epics / stories / tasks aligned to architecture and performance goals.
- Coordinate build and release schedule and web app deployments (TypeScript / React / Node or similar) across environments.
- Quality & Release Management
- Manage external QA resources; define test strategy, coverage goals, and entry / exit criteria per release.
- Work with contract and / or AI-based quality measures.
- Orchestrate regression, performance, and security testing; ensure defects are triaged with clear SLAs.
- Own release notes, change approval, and production readiness checklists.
- AI-Assisted Development Enablement
- Promote responsible use of AI coding tools (e.g., cursor.ai) to speed delivery.
- Track impact on velocity and quality; iterate practices based on evidence.
- Proactively surface risks, blockers, and decisions; drive mitigations with owners and dates.
- Liaise with the VP of R&D via daily concise reports and structured weekly updates; escalate early and with options.
- Align engineering, product, design, and QA around scope, tradeoffs, and timelines.
- Process Improvement
- Apply Lean principles to remove waste and reduce WIP; keep teams focused on the smallest shippable value.
- Evolve team health rituals; ensure clarity of roles, ownership, and working agreements.
Qualifications
- 5+ years in Technical Project / Program Management delivering SaaS products in production.
- Working knowledge of modern SaaS pipelines / builds and TypeScript -based modern web development (e.g., React / Next.js, Node).
- Practical experience with AWS and microservices.
- Strong Agile execution (Scrum / Kanban), backlog management, story slicing, and acceptance criteria writing.
- Proven ability to translate roadmaps into epics / stories / tasks and drive cross-functional execution to deadlines.
- Comfortable reading code, discussing architectures, and facilitating technical trade-offs.
- Experience coordinating external QA vendors and managing multi-environment release schedules.
- Demonstrated adoption of AI-assisted development with measurable impact on velocity / quality.
Not Mandatory, But We Would be Strongly Influenced By…
- Background in immersive / 3D applications or real-time systems.
- AI assisted-coding success stories that can scale the team
Success Metrics (First 90–180 days)
- 90% sprint goal attainment with ≤10% scope churn mid-sprint.
- 20–30% improvement in lead time / cycle time via waste removal and AI enablement.
- Reduction in escaped defects and MTTR; stable deployment frequency.
- Predictable release cadence with zero critical-release surprises.
Remote-first with core hours overlapping North America. Occasional travel for planning / on-sites (≤10%). Competitive compensation and benefits commensurate with experience.