Technical Project Manager - AI & CX TransformationLocation: Remote USA
Full-Time Contract 1099
Role OverviewThe Project Manager is responsible for leading the successful delivery of complex CX, CCaaS, AI, and digital transformation programs for enterprise and mid-market clients.
This role owns delivery from mobilization through implementation, go-live, and ongoing optimization. The Project Manager will coordinate multiple workstreams including architecture, engineering, integrations, data, AI/automation, testing, change management, and operational readiness.
The ideal candidate is a strong delivery leader who can operate comfortably between business stakeholders and technical teams. They do not need to be an AI engineer, but they must understand how modern AI solutions are designed, implemented, measured, governed, and adopted while being able to translate technical concepts into clear business decisions and outcomes.
Our Project Manager WillLMA (Lead, Manage, Accountability) - Own end-to-end delivery of complex transformation programs from mobilization through deployment and post-go-live optimization, ensuring accountability for scope, timeline, budget, quality, and outcomes
- Lead cross-functional teams across project management, architecture, engineering, AI, data, integrations, operations, and client stakeholders
- Establish clear responsibilities, expectations, dependencies, and decision rights across all stakeholders
- Drive a culture of accountability, transparency, collaboration, and continuous improvement
- Bring structure and clarity to complex and ambiguous transformation environments
- Adapt delivery methodologies (Agile, Waterfall, or hybrid) based on the needs of each engagement
Lead Program Governance & Project Workstreams - Establish and enforce governance standards, including executive steering committees, risk reviews, delivery cadences, status reporting, and project documentation
- Maintain RAID logs, program pulse, project plans, decisions, dependencies, and action tracking
- Identify risks, dependencies, and issues early; develop mitigation plans and escalate appropriately
- Oversee multiple workstreams and ensure alignment to program objectives, milestones, and client outcomes
- Ensure meetings result in clear decisions, owners, actions, and timelines
- Drive accountability across internal teams, vendors, and client stakeholders
Lead AI & Emerging Technology Delivery - Lead delivery of AI-enabled CX solutions, including conversational AI, generative AI, AI agents, automation, agent assist, and intelligent customer engagement capabilities
- Coordinate delivery across solution design, configuration/build, testing, UAT, production deployment, and post-launch optimization
- Support delivery of AI solutions that leverage enterprise knowledge bases and RAG, ensuring appropriate dependencies across content, data, integrations, and platform capabilities
- Coordinate with technical teams to identify data readiness requirements, including data sources, quality, accessibility, security, and dependencies
- Partner with architects, engineers, product teams, and AI specialists to ensure technical decisions remain aligned with business objectives and delivery requirements
- Translate capabilities, limitations, and technical dependencies into clear implications for clients and executive stakeholders
Lead AI Performance, Risk & Governance - Establish measurable success criteria for AI initiatives before implementation
- Track AI and business performance metrics such as accuracy, containment, task completion, adoption, latency, quality, and customer experience outcomes
- Monitor AI-specific delivery risks, including hallucinations, data quality issues, model limitations, integration dependencies, context limitations, and customer expectation gaps
- Partner with technical and client teams to establish appropriate testing, evaluation, guardrails, and quality controls
- Ensure AI initiatives consider security, privacy, governance, and appropriate handling of sensitive information
- Identify gaps between expected and actual AI performance and drive remediation plans
- Use delivery and performance data to inform prioritization and support continuous improvement
Lead Leadership & Client Relationships - Act as a primary interface for client stakeholders and executive leadership
- Lead executive-level meetings with clear, concise, and data-driven updates
- Build trust with technical and executive stakeholders through credibility, transparency, and strong communication
- Proactively surface risks, decisions, trade-offs, and opportunities requiring leadership attention
- Partner with Sales and Delivery teams to support ongoing and future client opportunities
- Capture customer feedback and delivery insights that can inform future solutions, services, and client roadmaps
Build Program Plans & Level of Effort - Develop and maintain detailed program plans, including timelines, milestones, dependencies, resource forecasts, and allocation
- Ensure project plans are accurately forecasted and updated weekly
- Proactively manage resource planning across multiple projects, ensuring visibility into demand and capacity
- Drive short-term planning discipline by reviewing and aligning 2-6-week sprint planning across delivery teams
- Support Level of Effort estimates, project financials, and SOW development
- Manage project resources against forecasted hours and assumed project timelines
- Ensure accurate revenue realization by managing billing milestones with clients and vendors
- Identify delivery impacts of scope changes and support change-order management
Lead Adoption, CSAT & Value Realization - Own CSAT throughout the program lifecycle
- Establish and track customer KPIs and success metrics
- Monitor delivery health and proactively address gaps
- Lead post-go-live reviews and value realization activities
- Support customer adoption of new technology, AI capabilities, and operational processes
- Coordinate feedback, training, and change-management activities as required
- Identify opportunities for continuous improvement and expansion
- Ensure consistent delivery of high-quality outcomes aligned to the client's business objectives
Our Ideal Candidate Will - Have 5+ years of experience in project or program management within enterprise technology, digital transformation, CX, CCaaS, SaaS, AI, or consulting environments
- Have experience leading complex, customer-facing technology programs with multiple technical and business workstreams
- Have experience working with AI, automation, conversational AI, GenAI, analytics, or emerging technology initiatives
- Understand the lifecycle of an AI-enabled solution from use-case definition through implementation, testing, deployment, and optimization
- Be comfortable working with technical teams across architecture, engineering, integrations, data, AI, and product
- Understand core concepts related to AI agents, conversational AI, LLMs, RAG, knowledge bases, automation, and AI-assisted customer experiences
- Be able to understand and discuss AI performance metrics and translate them into business outcomes
- Demonstrate excellent verbal and written communication skills with the ability to translate complex technical and AI concepts to non-technical audiences
- Have demonstrated success leading cross-functional project teams in complex or ambiguous environments
- Be highly organized and capable of managing multiple priorities, dependencies, and stakeholders simultaneously
- Have experience managing project budgets, resource forecasts, Level of Effort estimates, and/or SOWs
- Be comfortable working directly with senior client stakeholders and executive leadership
- Be proficient in Microsoft products and modern project/delivery management tools
- Have experience with Agile, Waterfall, or hybrid project delivery methodologies
Preferred Qualifications - PMP, PMI-ACP, Scrum Master, or related project management certification
- Experience with NICE CXone, Cognigy, or other CCaaS/CX platforms
- Experience delivering conversational AI, AI agents, agent assist, GenAI, or automation solutions
- Experience with enterprise AI use cases within customer experience or contact center environments
- Familiarity with LLMs, RAG, NLU/NLP, AI orchestration, knowledge management, or voice/digital AI technologies
- Experience with cloud platforms such as AWS, Azure, or GCP
- Experience with Salesforce, ServiceNow, Jira, Confluence, Smartsheet, Power BI, Rocketlane, or similar enterprise platforms
- Familiarity with AI governance, responsible AI, security, privacy, and model evaluation concepts
- Experience supporting technology roadmap development or solution strategy
- Experience working within a consulting, systems integration, or professional services organization
