Engagement Lead

About Deliverance AI

Deliverance AI is the production AI platform company. We exist because 94% of enterprises fail to scale AI — not for lack of ambition or budget, but for lack of platform, governance, and delivery capability. We close the gap between AI investment and AI production for enterprises across regulated industries including pharma and biotech, financial services, retail, telecommunications, and logistics.

Our proprietary nine-layer platform — built around three core capabilities: Clarity (see everything), Govern (control everything), and Accelerate (ship everything) — is deployed inside customer environments with live workloads running on it from day one. We are not a consultancy that writes strategy decks. We are not a staffing firm that lends contractors. We are an engineering-led company with proprietary platform IP, a growing agent marketplace, and 15+ pre-built AI blueprints that cut months off delivery timelines.

Our engagement model is simple: Assess (4 weeks), Deploy (12–16 weeks), Operate (ongoing). Dedicated engineering pods own delivery end-to-end. Every deployment compounds the platform. Every use case ships faster than the last. Governed, observable, and delivering value from day one.

About the role

The Engagement Lead is the single point of accountability for every customer engagement at Deliverance AI. You will own the end-to-end delivery lifecycle — from the initial 4-week Assessment through platform deployment and into ongoing operations — ensuring that every enterprise customer gets AI into production, not just another strategy deck.

This role sits at the heart of our Assess → Deploy → Operate model. You will lead discovery workshops that surface shadow AI, identify the highest-value use cases, and build architecture blueprints. You will then orchestrate a dedicated engineering pod (AI Architect, ML Engineer, Data Engineer) through a gated deployment process that puts 2–3 production workloads live within 12–16 weeks. And you will manage the transition into managed services, ensuring the customer realises compounding value over time.

This is not a traditional project manager role. You need enough technical depth to hold credible conversations with CTOs, VPs of Engineering, and Heads of AI at enterprises with £1B+ revenue. You also need the commercial awareness to manage scope, margins, and expansion. The Engagement Lead is always ours — non-negotiable. You own the delivery outcome.

What you will do

• Own the full delivery lifecycle for enterprise AI engagements across the Assess → Deploy → Operate model, from initial scoping through production go-live and ongoing hypercare.
• Lead hands-on Assessment workshops that identify use cases ranked by business impact and technical feasibility, surface governance gaps and shadow AI, and produce architecture blueprints mapped against our Clarity, Govern, and Accelerate capabilities.
• Build, resource, and manage cross-functional engineering pods comprising AI Architects, ML Engineers, and Data Engineers — delivered as a unit, not as individual contractors.
• Drive engagements through four gated deployment phases: Architecture & Design (weeks 1–3), Platform Build (weeks 3–10), Workload Onboarding (weeks 8–14), and Operationalise (weeks 12–16).
• Act as the primary escalation point and trusted advisor for enterprise customers, ensuring alignment between platform deployment and measurable business outcomes.
• Manage commercial aspects of engagements including change requests, scope adjustments, and identifying expansion opportunities that deepen the customer relationship.
• Deliver executive readouts that drive high conversion from Assessment to Deployment, and from Deployment to Operate.
• Coordinate with strategic partners on joint delivery motions, ensuring seamless handoffs between infrastructure provisioning and platform deployment.
• Contribute to the continuous improvement of our delivery methodology, blueprints, and engagement playbooks.

What we are looking for

• 7+ years of experience leading complex technology delivery engagements in enterprise environments — consulting, professional services, or systems integration backgrounds strongly preferred.
• Demonstrable experience delivering AI, data platform, or cloud infrastructure projects for regulated industries such as pharma, financial services, telecoms, or government.
• Strong technical literacy — you do not write code daily, but you can engage credibly on topics like inference infrastructure, model lifecycle management, RAG architectures, agent governance, and compliance-as-code.
• Proven ability to manage multiple concurrent engagements with distributed engineering teams, balancing delivery velocity with quality and margin targets.
• Exceptional stakeholder management skills — comfortable presenting to C-level executives and navigating multi-stakeholder organisations where CTOs, CISOs, CDOs, and procurement all have a voice.
• Experience with delivery frameworks including Agile, SAFe, or hybrid methodologies, with a pragmatic approach that adapts process to context rather than enforcing rigid ceremony.
• Familiarity with EU AI Act compliance requirements, UK regulatory landscapes (FCA, ICO/GDPR, MHRA/GxP, Cyber Essentials), and how governance translates into production architecture.
• A builder's mentality — you are joining a company where the delivery methodology is still evolving, and you will shape it as much as execute it.