Key Responsibilities

Program & Delivery Management

Own the delivery of OFC’s technology programs across engineering, product and operations — managing scope, timelines, budgets and resources across multiple concurrent workstreams.
Apply the right delivery methodology for each program, and evaluate and embed AI-assisted delivery practices — such as automated status reporting, intelligent dependency tracking and AI-augmented retrospective analysis — where they genuinely improve outcomes.
Break complex programs into manageable streams, plan capacity realistically, sequence dependencies and keep the team focused on the work that matters.
Track progress against milestones, identify roadblocks early, drive resolution, and maintain accurate delivery forecasts that the leadership team can rely on.

Communication, Transparency & Stakeholder Engagement

Use both formal and informal communication to drive delivery transparency across the company and to our customers — ensuring teams, leaders, partners and (where relevant) customers have a clear, timely and honest view of progress, risks, dependencies and the decisions required.
Act as the primary delivery interface to OFC’s senior leadership, partners and customers — pairing structured executive reporting with the everyday hallway conversations that keep delivery honest.
Translate technology delivery into language non-technical stakeholders can engage with, including communicating delivery programs that incorporate AI tooling adoption in terms stakeholders can actually evaluate and act on.
Manage stakeholder expectations actively — surfacing trade-offs early, escalating when needed, and protecting the team from churn caused by avoidable ambiguity.
Build strong, trust-based working relationships with the engineering, product, design, QA, DevOps and operations functions, and with our partners and suppliers.

Risk, Dependency & Issue Management

Identify, escalate and manage delivery risks, dependencies and issues proactively — including risks specific to AI tooling adoption, such as vendor concentration, data governance exposure, AI-generated artefact quality, compliance considerations and team capability gaps in responsible AI use.
Develop and own mitigation plans, with clear ownership, timelines and decision points.
Coordinate across vendors, partners and integration counterparties to manage external dependencies that affect delivery confidence.
Lead post-incident and post-program reviews where appropriate, turning lessons into durable improvements in how OFC delivers.

Delivery Governance, Innovation & Continuous Improvement

Identify opportunities to improve delivery governance, reporting and operating rhythms in ways that genuinely benefit the team and the business.
Lead the responsible exploration of AI-assisted delivery practices — such as automated status reporting, intelligent dependency tracking and AI-augmented retrospective analysis — bringing an informed, critical view on where they genuinely add value and where they don’t.
Establish and uphold delivery governance appropriate to a scaleup — light enough to move fast, strong enough to keep us honest, and tailored to the regulated payments and mobility environment OFC operates in.
Maintain and evolve the delivery operating model as OFC scales, including planning and estimation practices that account for AI-assisted engineering, quality and operational workflows.
Manage delivery budgets, resource plans and vendor contracts, including cost modelling for AI tooling investment and the productivity assumptions used to justify it.

Collaboration & Capability

Partner closely with the Head of Engineering, the Technical Product Manager, the DevOps Lead, the QA Lead and other engineering and product leaders to plan and execute against OFC’s roadmap.
Coach engineering and product teams on disciplined delivery practice without micromanaging — lifting the team’s collective delivery capability over time.
Champion the additional coordination overhead that responsible AI tooling governance introduces into delivery planning, and make sure it’s accounted for honestly in plans and estimates.
Contribute to the broader OFC engineering culture — clear thinking, honest communication, and a genuine focus on outcomes for our partners and customers.

What you’ll bring

To succeed in this role, you will bring:

Qualifications

High emotional intelligence and strong soft leadership capability — you recognise the strengths of engineering, product, QA and DevOps teams, and create the conditions for those strengths to contribute to shared business outcomes through influence and trust rather than authority.
Strong modern delivery fundamentals, with the comfort and confidence to operate across multiple delivery methodologies — knowing which is right for which program and how to adapt as conditions change.
Excellent communication capability across formal and informal channels, with the ability to drive delivery transparency across the company and to our customers — ensuring stakeholders have a clear, timely and honest view of progress, risks, dependencies and decisions required.
Strong program and delivery management capability, with demonstrated experience delivering complex technology programs in fast-moving environments, and the risk and dependency discipline to identify and mitigate delivery risks proactively — including the specific risks introduced by AI tooling adoption in modern technology delivery.
Thoughtful creativity and a practical, responsible mindset toward innovation, with the judgement to identify opportunities to improve delivery governance, reporting and operating rhythms — particularly through the responsible exploration of AI-assisted delivery practices.

Experience

7 to 10 years in IT or technology roles, with at least 3 to 5 years in delivery management, program management or equivalent positions.
Demonstrated experience delivering complex technology programs on time and within budget — ideally including programs where AI-assisted engineering, quality or operational practices were in use and where delivery governance adapted accordingly.
Practical experience managing delivery budgets, resource plans and vendor contracts — including, where applicable, vendor and contract considerations relevant to AI tooling and AI platform service providers.
Hands-on experience using modern delivery tooling (e.g. Jira, Confluence, Linear, MS Project, equivalent) alongside emerging AI-assisted delivery and reporting platforms, with a disciplined approach to validating AI-generated insights before they inform stakeholder decisions.
Experience operating in product-led SaaS, fintech, payments, mobility or other regulated technology environments is highly desirable.
PMP, PRINCE2, Scrum/SAFe or equivalent certifications are valued — and so is the practical wisdom to know which parts of any methodology are worth keeping.

Skills

Soft leadership in practice — reading the room, recognising team strengths, building trust quickly, and creating the conditions for cross-functional teams to do their best work.
Delivery methodology fluency across agile, waterfall and hybrid approaches.
Communication across channels — executive reporting, verbal updates, written briefs, escalation, hallway conversations, and the everyday transparency that keeps delivery honest.
Project and program management tooling — Jira, Confluence, MS Project or equivalent — alongside familiarity with AI-augmented portfolio and delivery intelligence platforms applied with appropriate validation.
Responsible innovation in delivery practice — identifying opportunities to improve governance, reporting and operating rhythms, and exploring AI-assisted approaches with both creativity and discipline.
Vendor and contract management, including governance considerations specific to AI tooling vendors, platform service providers and AI-assisted managed service arrangements.
Financial planning, budget tracking and resource management, including cost modelling for AI tooling investment and cloud workload expenditure.
Risk management, dependency tracking and issue resolution across complex, multi-team programs.
Coaching and capability uplift — helping engineering, product, QA and DevOps teams strengthen their own delivery practice over time.