Accellor—Senior Delivery Manager / Delivery Lead

Job description

Description: We are looking for a delivery leader to own the end-to-end execution of our AI & 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 sizeable embedded team. At other times you will run a portfolio of two to three smaller engagements in parallel, typically 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 on programs that are watched closely by senior enterprise stakeholders. What makes this role different: these are agentic and GenAI builds, not deterministic IT projects. “Done” is defined by evaluations, guardrails, and human-in-the-loop validation rather than a fixed spec. We need a delivery leader who understands that reality in their bones — who can plan around non-determinism, set honest expectations with clients, and recognise the difference between what is genuinely production-ready and what is still aspirational. Key responsibilities: Delivery execution & 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 & 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 & 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 & 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 & 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 & 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.