Senior IT Project Manager – AI & Automation Transformation (Telco Managed Services)
Location: Hybrid / Remote (Canada preferred)
Role Overview:
We are seeking a forward-thinking Senior IT Project Manager to lead a large-scale AI-driven managed services transformationwithin a telecommunications environment. This role will focus on delivering intelligent automation and engineering enablement capabilities, leveraging agentic AI frameworks, machine learning, and advanced orchestration technologies to transform IT and network operations.
You will play a pivotal role in embedding AI-first operating models, enabling autonomous workflows, and accelerating digital transformation across IT systems, platforms (including ServiceNow), and network domains.
Key Responsibilities:
AI Transformation & Automation Leadership:
- Lead the design and delivery of AI-powered automation initiatives, including agentic AI frameworks for autonomous decision-making and workflow execution.
- Define and execute the roadmap for AI adoption across IT and network operations, aligned to managed services transformation goals.
- Drive use case identification, prioritization, and industrialization of AI solutions (e.g., predictive operations, intelligent ticketing, self-healing systems).
- Establish governance models for responsible AI, model lifecycle management, and performance monitoring.
Agentic AI & Engineering Enablement:
- Enable adoption of agent-based AI architectures to orchestrate complex workflows across multiple systems.
- Collaborate with engineering teams to integrate LLMs, AI agents, orchestration layers, and decision engines into enterprise platforms.
- Drive implementation of automation frameworks leveraging APIs, event-driven architectures, and AI pipelines.
- Promote development of reusable AI services, tools, and accelerators for scale.
Integration & Platform Delivery:
- Oversee integration of AI capabilities with enterprise platforms, including ServiceNow, OSS/BSS, and cloud ecosystems.
- Ensure seamless interoperability between AI components, IT systems, and network platforms.
- Lead delivery of data pipelines and integration frameworks required to support AI models and automation.
- Partner with architecture teams to ensure scalability, security, and resilience of AI-enabled solutions.
Program & Stakeholder Management:
- Lead end-to-end program delivery across multiple AI and automation workstreams.
- Engage senior stakeholders to define AI strategy, business value, and transformation outcomes.
- Manage cross-functional teams including data scientists, AI engineers, developers, and system integrators.
- Drive executive reporting, governance forums, and value realization tracking.
Vendor & Ecosystem Management:
- Manage relationships with AI technology vendors, platform providers, and system integrators.
- Evaluate and onboard emerging AI tools, frameworks, and platforms.
- Ensure alignment between vendor capabilities and enterprise AI strategy.
Risk, Governance & Financial Management:
- Identify and mitigate risks related to AI adoption (e.g., model bias, data privacy, regulatory compliance).
- Manage budgets, resource plans, and ROI tracking for AI initiatives.
- Establish KPIs for automation efficiency, AI adoption, and operational impact.
Required Qualifications:
- 8–12+ years of experience in IT project/program management, with recent focus on AI or automation-led transformation.
- Proven experience delivering AI/ML or intelligent automation programs in large enterprises.
- Experience implementing or managing agentic AI frameworks, conversational AI, or autonomous systems.
- Strong background in system integration and enterprise architecture.
- Experience in telecommunications or managed services environments (preferred).
Technical & Domain Expertise:
- AI/ML technologies (LLMs, NLP, predictive analytics, computer vision – as applicable).
- Agentic AI frameworks and orchestration platforms.
- Automation technologies (RPA, workflow orchestration, event-driven systems).
- API-led integration, microservices, and middleware platforms.
- Cloud platforms (AWS, Azure, GCP) and AI/ML services.
- Data engineering (data pipelines, streaming, data lakes).
- Familiarity with ServiceNow as an integration and workflow platform (secondary focus).
- Knowledge of OSS/BSS systems in telecom (preferred).
Leadership & Soft Skills:
- Strong ability to translate AI capabilities into business value and operational outcomes.
- Excellent stakeholder management, including executive-level communication.
- Ability to lead multidisciplinary teams (AI, engineering, operations).
- Strategic thinking with hands-on delivery orientation.
- Strong problem-solving skills in complex, ambiguous environments.
Preferred Certifications:
- PMP, PgMP, or PRINCE2.
- AI/ML certifications (e.g., AWS Certified Machine Learning, Azure AI Engineer).
- SAFe Agilist / Scrum certifications.
- Relevant certifications in data, cloud, or automation technologies.
Success Metrics:
- Successful deployment of AI-driven automation use cases at scale.
- Reduction in manual operations through autonomous workflows and AI agents.
- Measurable improvements in operational KPIs (MTTR, incident volumes, cost efficiency).
- Adoption and reuse of AI-enabled services across teams.
- Demonstrated ROI and business value from AI investments.
Nice-to-Have:
- Experience with AIOps, self-healing networks, or autonomous operations.
- Exposure to GenAI-based copilots and enterprise AI platforms.
- Understanding of AI governance, ethics, and regulatory considerations.