About this role
Manage end-to-end delivery of IT projects, with a focus on integrating AI/ML solutions into enterprise systems. Lead Agile (and/or hybrid) execution, coordinate cross-functional stakeholders, and ensure governance, data privacy, and ethical AI standards are met.
Key Responsibilities
- Lead end-to-end delivery of IT projects including AI/ML integration initiatives from planning through post-deployment support. Manage project scope, timeline, budget, risks, and dependencies across multiple concurrent initiatives. Translate AI/ML use cases into executable project plans with cross-functional teams. Coordinate integration of AI/ML models into enterprise systems including applications, data platforms, and APIs. Drive Agile and/or hybrid delivery (sprint planning, stand-ups, retrospectives) and ensure governance, data privacy, and ethical AI compliance.
Technical Overview
This PM role works directly with AI/ML teams to translate AI/ML use cases into executable project plans. It coordinates integration of AI/ML models with applications, data platforms, and APIs while managing technical, data, security, and compliance risks across deployment and post-deployment support.
Ideal Candidate
The ideal candidate is a mid-level IT Project Manager who has led end-to-end delivery of AI/ML integration initiatives from planning through post-deployment support. They are comfortable driving Agile (and/or hybrid) delivery practices, coordinating cross-functional teams, and managing technical, data, security, and compliance risks for ethical AI and data privacy governance.
Must-Have Skills
Lead end-to-end delivery of IT projectsincluding AI/ML integration initiativesfrom planning through implementation and post-deployment support.Manage project scopetimelinebudgetrisksand dependencies across multiple concurrent initiatives.Drive Agile and/or hybrid delivery methodologiesfacilitating sprint planningstand-upsretrospectivesand status reporting.Partner with data scientistsengineersarchitectsproduct ownersand business stakeholders to translate AI/ML use cases into executable project plans.Identify and mitigate technicaldatasecurityand compliance risks associated with AI/ML deployments.Ensure adherence to governancedata privacyand ethical AI standards.
Tools & Platforms
AgileAI/ML modelsAPIsdata platforms
Required Skills
end-to-end delivery of IT projectsAI/ML integration initiativesproject scopetimelinebudgetrisksdependenciesAgile delivery methodologiessprint planningstand-upsretrospectivesstatus reportingpartner with data scientistsengineersarchitectsproduct ownersbusiness stakeholdersintegrate AI/ML models into enterprise systems (applicationsdata platformsAPIs)mitigate technical/data/security/compliance risksgovernancedata privacyethical AI standardscommunicate project status to leadership and executive stakeholderscontinuous improvement of project management practicestoolingdelivery frameworks
Hard Skills
end-to-end delivery of IT projectsAI/ML integration initiativesproject scope managementtimeline managementbudget managementrisk managementdependency managementAgile delivery methodologieshybrid delivery methodologiessprint planningstand-upsretrospectivesstatus reportingintegration of AI/ML modelsenterprise systems integrationapplications integrationdata platform integrationAPI integrationtechnical risk identificationdata risk identificationsecurity risk mitigationcompliance risk identificationgovernancedata privacyethical AI standardsexecutive stakeholder communication
Soft Skills
lead end-to-end deliveryfacilitate sprint ceremoniescross-functional collaborationcommunicationrisk mitigation leadershipstakeholder managementcontinuous improvement advocacypartnering with business stakeholderstranslating AI/ML use cases into executable project plans
Keywords for Your Resume
IT Project ManagerProject Managerend-to-end deliveryIT projectsAI/ML integrationAI ML integrationproject scopetimelinebudgetrisksdependenciesAgile deliveryhybrid delivery methodologiessprint planningstand-upsretrospectivesstatus reportingdata scientistsengineersarchitectsproduct ownersbusiness stakeholdersintegration of AI/ML modelsenterprise systemsapplicationsdata platformsAPIsgovernancedata privacyethical AIcontinuous improvementpost-deployment support
Deal Breakers
Must have led end-to-end IT project delivery including AI/ML integration initiatives, Must have experience driving Agile delivery including sprint planning, stand-ups, and retrospectives, Must have experience mitigating technical, data, security, and compliance risks for AI/ML deployments
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