About this role
The Head of Delivery is the architect and steward of Capptus’ delivery operating system.
Their mission is to design a delivery environment where:
AI removes execution friction Human judgment, taste, and systems thinking drive decisions Small, high-leverage teams consistently outperform larger, siloed ones Knowledge compounds across projects instead of resetting each time
Core Responsibilities (AI-First & System-Led): 1. Design the AI-First Delivery System (Primary Responsibility)
Define how work flows from idea → delivery → learning:
Where AI assists exploration, design, testing, and documentation Where human review and judgment are mandatory Where decisions must be explicit, documented, and reversible
Ensure all delivery roles operate in shared mediums:
Same artifacts Same tooling Same understanding of context Minimal handoffs
2. Elevate Judgment as the Core Delivery Skill
Redesign delivery expectations so senior roles are evaluated on:
Quality of architectural decisions Tradeoff clarity Ability to frame problems, not just solve tasks
Institutionalize judgment rituals:
Lightweight decision reviews Explicit assumptions and risk articulation “What would make this decision wrong?” discussions
Protect time for thinking:
Architects and leads are not fully utilized
Slack is intentional, not waste Judgment degrades under constant execution pressure
3. Operate Delivery as a Living System
Treat delivery as:
Inputs (scope, constraints, talent, customer context) Flow (work in progress, dependencies, decisions) Outputs (value, quality, margin) Feedback (learning, reuse, improvement)
Identify and act on:
Bottlenecks Feedback delays Misaligned incentives Over-optimization of local metrics
Use data (including Certinia) as signals, not commands.
4. Certinia as Observability, Not Control
Surface patterns and constraints Track financial and delivery reality Enable fast, informed decisions
5. Knowledge as a System Output
Every project must produce:
Reusable patterns Decision rationales What-worked / what-didn’t insights
AI is used to:
Extract learning from delivery artifacts Summarize complex projects Connect current teams with prior context
Knowledge ownership is explicit:
Assets are curated, pruned, and reused Learning feeds back into future delivery design
6. Talent Development for Systems Thinkers
What the HoD Builds
Consultants and developers who:
Understand the full delivery system Can reason across data, platform, business, and customer context Specialize deeply in judgment-heavy domains
Clear progression:
From task execution → problem framing → system ownership → mentorship
Juniors are onboarded into thinking, not just doing:
Early exposure to decisions Explicit explanation of tradeoffs AI used as a learning accelerator
7. Customer as Part of the System
Customers are treated as:
Active participants in delivery Decision-makers with constraints Sources of feedback, not interruptions
SteerCos are:
Alignment forums Constraint-renegotiation spaces Shared judgment environments
Leadership Expectations
Optimize for long-term leverage, not short-term output Make invisible work visible (decisions, tradeoffs, learning) Use AI comfortably without surrendering responsibility Protect buena onda while holding high standards
Think like a system architect, not a project manager.