Delivery Manager

We are looking for a delivery leader to own the end-to-end execution of our AI and Data engagements for large enterprise clients, Fortune 500 and Fortune 100 organisations across industries. These are high-stakes transformation programs where the work spans agentic AI, generative AI, and modern data platforms.

The role flexes by program shape. At peak, you may run a single large, multi-POD program with a sizable embedded team. At other times, you will run a portfolio of two to three smaller engagements in parallel, typically with five to eight people each. We expect you to be equally comfortable orchestrating a large team through governance and cadence, and staying hands-on across several smaller teams without dropping a thread.

You are accountable for delivering to plan, keeping teams efficient and well-utilised, protecting delivery quality, and sustaining client confidence in programs that are watched closely by senior enterprise stakeholders.

The candidate will have responsibilities across the following functions:

Delivery execution and governance:

• Own end-to-end delivery of one large program or 2-3 parallel engagements against committed scope, timeline, and quality.
• Run the delivery rhythm: planning, sprint cadence, status reporting, risk and dependency management, and escalation discipline.
• Keep delivery on plan; flag scope creep, slippage, and risk early and credibly.

Agentic and GenAI delivery leadership:

• Lead delivery of agentic and GenAI solutions, applying the right rigour to non-deterministic systems evaluations, guardrails, model/version drift, and human-in-the-loop gating.
• Set realistic, honest expectations with clients on what agentic systems can and cannot do today.
• Partner with the AI Labs and POD teams to move solutions from pilot to production reliably.

Team and POD leadership:

• Lead and coach POD leads, Forward Deployed Engineers, and engineering teams; set standards and unblock the team.
• Manage staffing, ramp-up, and clean resource movement across engagements as priorities shift.
• Be the most senior delivery presence in the room, technically credible enough that the team respects your judgement.

Client and stakeholder management:

• Be the trusted delivery point of contact for senior client stakeholders, including CIO-, VP-, and director-level.
• Translate between client objectives and technical reality; protect the relationship while holding firm on scope and quality.
• Navigate a multi-vendor environment and keep the engagement positioned as a confident, neutral advisor.

Delivery health and efficiency:

• Keep teams efficient and right-sized; manage utilisation and cost discipline within the agreed staffing envelope.
• Surface commercial risks (scope creep, change requests, staffing pressure) early to the Practice Head.

Requirements:

• 10+ years total experience, with 5+ years in delivery leadership inside a services or consulting model.
• Demonstrated track record running both a large, multi-team program and parallel engagements, so the flex between the two modes is proven, not aspirational. Genuine, hands-on understanding of agentic and GenAI delivery: evaluations, guardrails, human-in-the-loop, and the realities of shipping non-deterministic systems.
• Strong overall technical depth, these are complex, production-grade agentic AI applications, and the delivery lead must be able to engage credibly on architecture, integration, and engineering trade-offs, not just process.
• Familiarity with common multi-agent frameworks and orchestration patterns (e. g., LangGraph, AutoGen, CrewAI, Semantic Kernel) and the major cloud AI and data stacks (Azure, AWS, GCP).
• Credible data-platform delivery experience, having shipped a real data foundation (e. g., lakehouse / Fabric / Databricks / Snowflake or equivalent), not just consumed one.
• Solid understanding of business processes and how AI solutions map to real business outcomes, able to connect what the team builds to the value the client is after.
• Track record delivering for large enterprise clients (Fortune 500 / Fortune 100), with awareness of enterprise security, compliance, and data governance expectations at that scale.
• Strong senior-stakeholder presence and the ability to say no credibly when scope drifts.
• Player-coach posture: senior enough to own a portfolio, hands-on enough to earn the team's technical respect.

Nice-to-have:

• Delivery experience across multiple industries (high-tech, retail, manufacturing, financial services, healthcare).
• Relevant certifications (PMP, SAFe/Agile, cloud or AI platform certifications).
• Exposure to a POD-based, Forward-Deployed-Engineer delivery model.
• Comfort with global clients and time zones, and periodic travel.

Skills

AWS, Azure, Databricks, GCP, GenAI, Microsoft Fabric, Snowflake, agentic, generative AI, lakehouse