AI Engineering Lead Senior Manager - Multiple Teams

Purpose-led workyou’llbe part of

As aSenior Manager,you’lllead AI-enabled, data-driven engagements and help shape our market proposition. This is a role where strategy meets execution:you’llown solution direction from discovery and design through build,deploymentand adoption; bridge business needs with technical implementation; and translate emerging AI capabilities into practical,governedand scalable outcomes.

Role & Responsibilities:

AI Solution Delivery 

• Lead multi-workstream AI engagements end-to-end— from solution design through production deployment — across use cases such as intelligent document extraction, automated variance analysis, compliance agents, and generative AI workflows

• Architect and assure technical solutionsacross data platforms, integration patterns, and deployment approaches, ensuring designs are secure, scalable, cost-conscious, and production-grade

• Apply AI and advanced analytics to unstructured data challengesin remediation, compliance, and large-scale document review contexts where auditability, traceability, and governance are non-negotiable

• Define target-state data and AI operating models— including governance, ownership, decision rights, Responsible AI controls, human-in-the-loop design, and data product management (lineage, quality, metadata, stewardship) — to ensure solutionsremaintrusted and usable beyond go-live

Delivery Management

• Engage withsenior client leadershipto define data strategy, assess control execution,identifyreporting gaps, and design future-state data capabilities aligned to business strategy

• Translate complex technical capabilities into clear business outcomes— quantifying value in terms of hours saved, manual effort eliminated, improved controls, enriched data quality, and strengthened auditability

• Ownprogrammegovernance and delivery excellenceincludingfinancial management,planning, RAID management, executive reporting/steerco packs, quality assurance, and benefits tracking

Practice & Commercial Growth

• Expand existing client relationshipsby converting proven delivery into repeatable, scalable opportunities — building pipeline from within active accounts and shaping longer-term commercial relationships grounded in tangible value

• Contribute toproposals,go-to-market and thought leadershipby shaping points of view, accelerators, demos, and case studies—translating delivery learnings into repeatable offerings

• Codify reusable delivery assets, governance approaches, and solution patterns drawn from live client work to accelerate future engagements and strengthen the practice

Team Leadership & Culture

• Build team capability and culturethrough coaching, performance management, on-the-job training, and active contribution to hiring and onboarding

Your Profile:

Required:

• Proven end-to-end delivery of AI and data solutions into production(not just strategy or proof-of-concept), including applied experience in NLP/document extraction, generative AI workflows, or agent-based automation — with working knowledge ofMLOps/LLMOpspractices including evaluation, monitoring, and model lifecycle management

• Strongproficiencyin Python, SQL, and modern analytics engineering(e.g.,dbtor equivalent), including data modelling patterns and transformation pipeline orchestration for production-grade data and AI applications

• Strong leadership acrossteams—coach and develop technical consultants (onshore/nearshore/offshore) into high-performing delivery teams

• 8+ years’ experience in solution design and technical delivery, withrecent senior accountabilityfor outcomes across multiple workstreams

• At that the director level 15+ years’ experience isrequiredwithsignificant experiencewithin the Irish market

Preferred:

• Experience delivering in regulated environments(e.g., financial services, insurance, public sector) where governance, auditability, risk management, Responsible AI, data privacy, and security-by-design are non-negotiable

• Hands-onproficiencywith cloud data platforms— one or more of: Snowflake, Azure Data Services, Databricks

• Experience with modern deployment practices(CI/CD, testing, observability) andcontainerisedservices (Docker/Kubernetes) to support production-grade solutions

• Experience with low-code AI and automation tools:particularly Microsoft Power Platform, Microsoft Copilot Studio, and/or SalesforceAgentforce

• Data strategy and governanceexpertiseincluding operating model design, data ownership/stewardship, data quality management, lineage/metadata, access controls, and control/audit evidence

• Strong client leadership:able to shape problem statements, challenge constructively, and secure decisions with senior stakeholders in ambiguous environments

• Commercial aptitude:shaping scope, estimating, writing proposals, and managing engagement economics (margin, resourcing, and risk)