Technical Program Manager

Robots and Pencils

2d•CA$202,589 - CA$238,426•Remote

About The Position

Robots & Pencils is an applied AI engineering firm that designs and delivers AI co-workers for enterprise operations. The company works across industries including Consumer Products and Retail, Education, Energy, Financial Services, Healthcare, and Manufacturing, with delivery centers in Canada, the United States, Eastern Europe, and Latin America. The Technical Program Manager owns the full lifecycle of large, multi-workstream programs, translating client business goals into technical plans and guiding delivery through launch and realized value. The role connects business and engineering, facilitates architecture and engineering discussions, shapes technical direction with engineering leads, and aligns distributed teams around shared outcomes. Programs may involve enterprise AI, cloud, and agentic transformations, with responsibility for managing competing priorities, risks, stakeholders, and trade-offs. The position leads programs from strategy and roadmap through delivery, establishes program governance and KPIs, and ensures teams follow shared standards for AI development, evaluation, human review, monitoring, and reporting. It also serves as a senior partner to client executives, mentors delivery managers, contributes to the company’s delivery practices, and works with Client Partners on staffing and potential follow-on opportunities. The role is remote in Canada or the United States.

Requirements

At least 5 years of experience leading multiple Agile teams concurrently or at scale, including Scrum Masters and Product Owners.
At least 5 years of experience leading and delivering enterprise-level IT engagements.
A track record leading large-scale ($10M+) AI, digital, or cloud transformation programs from strategy through realized business value.
Practical application of frameworks such as Well-Architected and Cloud Adoption Framework to inform program decisions and solution governance.
A strong technical foundation and the ability to engage credibly on architecture, frontend and back-end technologies, and cloud-native design.
Ability to decompose complex technical problems into deliverable solutions and translate customer needs into technical requirements and functional specifications tied to business outcomes.
Experience leading programs where AI/ML or agentic capability was core to the solution, including management of model risk, evaluation, and client expectations.
Ability to set program-wide standards for AI evaluation, human-in-the-loop checkpoints, and monitoring.
Demonstrable daily use of AI tools such as Claude to improve planning, specifications, reporting, and documentation.
Experience with delivery and engineering tools such as Jira, Confluence, GitHub, Azure DevOps, and CI/CD pipelines.
Comfort operating amid ambiguity and credibility with clients to advance growth conversations with Client Partners.

Nice To Haves

Industry depth in one or more of Consumer Products and Retail, Education, Energy, Financial Services, Healthcare, or Manufacturing.
Experience delivering enterprise agentic, AI co-worker, or applied-AI initiatives.
Comprehensive knowledge of AWS services, architectures, and best practices, applied to technical decisions and strategic planning.
End-to-end delivery ownership of complex, multi-workstream agentic AI transformation programs.
Prior client-facing career experience in engagement management, consulting, or account leadership that informs growth conversations.

Responsibilities

Own end-to-end delivery of large-scale ($10M+) AI, digital, and cloud transformation programs from strategy and roadmap through launch and realized business value.
Break complex programs into manageable workstreams with clear ownership, sequencing, and dependencies.
Drive schedules across multiple concurrent Agile teams and maintain an integrated plan with delivery managers and product managers.
Define program-level KPIs and governance, report program health, and guide decisions about scope, timeline, budget, and quality.
Translate customer needs into technical requirements and connect those requirements to business outcomes.
Facilitate engineering and architecture discussions and help guide teams’ technical direction.
Decompose complex technical problems into actionable solutions and contribute to technical documentation and program documentation standards.
Own the AI Development Life Cycle at the program level and establish standards for Senior Delivery Managers to apply across workstreams.
Set program-wide definitions of done for AI-driven features, including evaluation thresholds, human-in-the-loop checkpoints, and post-launch monitoring.
Partner with AI engineering leads on model risk, data readiness, evaluation strategy, and observability; translate uncertainty into plans and risk registers.
Define and track success measures for AI-augmented delivery, including quality, rework, review overhead, and velocity.
Assess whether an agentic approach is appropriate for a client, considering context management, latency, infrastructure, and cost, and explain the decision to the client.
Use AI tools such as Claude to support planning, specifications, reporting, and stakeholder communication, and model this practice for delivery leaders.
Serve as senior program partner to client executives and communicate transparently and consistently.
Anticipate bottlenecks, manage escalations, and make trade-offs that balance business needs and technical constraints.
Lead trade-off decisions with customers, stakeholders, and partner teams when priorities conflict or committed outcomes and quality are at risk.
Communicate schedules, progress, and business impact to stakeholders and senior leaders.
Partner with Client Partners on follow-on work and expansion opportunities.
Lead and mentor Senior Delivery Managers and Delivery Managers, providing concrete feedback and stretch opportunities.
Create clarity for teams working amid ambiguity and conflicting priorities.
Shape the company’s delivery practice, tools, and frameworks beyond assigned programs.
Assess program staffing and capability gaps and work with Client Partners and leadership on staffing needs and talent.
Conduct executive interviews and contribute to go/no-go hiring decisions across the firm.