60 Zappos.Com Technical Project Manager Jobs Hiring Near You

Role: Technical Project Manager (Should have GenAI / RPA Background)
Location: Toronto , Ontario , M5V 0S8 (Hybrid) OR MTV - 2535 Garcia Ave , Mountain View, CA 94043
Role: Technical Project Manager (Should have GenAI / RPA Background)
Location: Toronto , Ontario , M5V 0S8 (Hybrid) OR MTV - 2535 Garcia Ave , Mountain View, CA 94043
Introduction
Technical Project Manager that has extensive work experience with the completion of technical artifacts and partnering with Engineering teams to collect recommendations and approvals for the advancement of product and AI projects.
To be successful in this role, the candidate must be self-sufficient, internally driven, views constant change as a challenge and is motivated to overcome blockers. Framework is provided, however no micro-management will occur, therefore candidates need to be independent and enthusiastic about advancing a heavy project load rapidly. Virtual networking, navigating numerous internal resources and efficient project plan building will be the consistent experience and candidates proficient in these areas will be successful.
Our Engineering and Product team members will provide direction of what is desired and how they intend to advance the solution, however the completion of paperwork and collection of approvals will be the primary duty of the Technical Project Manager.
Required Skills
High-Level Design
This is the primary document that will need to be produced as the Technical Project Manager. The Technical Project Manager will be the (D)river within the DACIE (Driver, Approvers, Contributors, Informed and Escalation). Partnering with our Project Requestors, Product Manager, Process Architects and Program Manager on the Problem Statement, Constraints, Proposed Solution and Solution Design will be content that the Technical Project Manager is accountable to produce rapidly for all projects. This will include Architectural Decisions, Capability Architecture, Design Assumptions, Non Functional Requirements/Examples along with Security, SOX Compliance and Infosec Compliance.
Low-Level Design
This is the secondary document that will need to be produced as the Technical Project Manager. Similar to the High-Level Design, the Technical Project Manager will be the (D)river within the DACIE (Driver, Approvers, Contributors, Informed and Escalation). This document starts with a concise Executive Summary, advances to a Detailed Component Design, Decisions & Justifications, Operational & Quality Aspects and concludes with Risks, Open Questions & Future Work. The creation, collection and explanation of this content will be the responsibility of the Technical Project Manager.
Product Requirements Document
Focusing on the "Why" and not just the "What", being concise and collaborating early and often are the key fundamentals to a quality Product Requirements Document. There are 12 key areas that are covered and the best candidate will not only be familiar with all of these areas, but have recent past experience that verifies the ability to produce this content.

1. Introduction & Vision - Big picture, elevator pitch that is easily understood by technical and functional team members
2. Problem Statement - Pain points, users problem, "Jobs to be Done" framework
3. Goals & Objectives - What will this accomplish, clear/measureable goals, why is this worth the time and resources invested
4. Success Metrics - Not only what will be measured, but the creation of the dashboard/report views
5. Personas & Scenarios - Who are we building this for, user-centric decisions, tell the story of what "before" is and what "after" will be and why this matters to each persona
6. Process Flows - Current 'AS IS' and future 'TO BE' workflows, must be end-to-end and in most cases is multi-org impacting
7. Requirements & User Stories - Features, functions and user-facing behaviors
8. Design & User Experience
9. Dependencies & Risks
10. Out of Scope, Future Work & Deferrals
11. Launch Plan / Project Plan
12. Q&A / Open Questions

Responsible Artificial Intelligence (RAI)
The Modern Technology Office (MTO) started off 7 years ago on the foundation of automation tools such as UiPath Robotic Process Automation (RPA) and Alteryx, over the past 3 years we have evolved into providing Generative AI and Agentic AI solutions. The Technical Project Manager will need to be well versed in advancing AI related projects within an enterprise setting. This will involve filling out AI technical forms, creating DevPortal assets, experience ID's and being accountable to answering Engineering inquiries on AI submissions. These questions will require reaching out to various resources via numerous methods to collect information in addition to being proficient in external searches typically with AI tool self-serve answers to be correlated back to the specific AI solution being advanced. There will be many instances where the Technical Project Manager will be the first to provide answers to new questions that will be foundational for how we shape our internal AI projects in the future. The best candidate will be comfortable being the first to explore a new technical capability and be motivated by the challenges associated with integrating backoffice AI solutions within a compliance heavy, FinTech environment.
Key Words/Phrases

• Communication
• Timelines
• Deliverables
• Solution Approach
• technical artifacts
• Artificial Intelligence
• AI
• Responsible Artificial Intelligence
• RAI
• High-Level Design
• Low-Level Design
• Product Requirements Document
• DACIE
• Architectural Decisions
• Motivate / Motivation
• Engagement / Participation
• Creative / Creativity
• Relationship Building
• Project Management
• Program Awareness
• Google Workspace
• Generative Artificial Intelligence
• GenAI
• ChatGPT
• GPT-4
• GPT-4-32K
• GPT-3.5 Turbo
• GPT-3
• Google Gemini
• Cogram
• Glean
• GenAI Parameters
• Chat Completion
• Prompt Design
• System Prompts
• Text Completion
• Embedding
• Large Language Model
• LLM
• GenPlugins
• GenUX
• GenRuntime
• GenStudio
• GenStudioPy
• Tokens
• Machine Learning
• ML