Engineering Manager

About Shelf

There is no AI Strategy without a Data Strategy. Getting GenAI to work is mission-critical for most companies, but 90% of AI projects haven't deployed. Why? Poor data quality - it is the #1 obstacle companies have in getting GenAI projects into production.

We've helped some of the best brands like Amazon, Mayo Clinic, AmFam, and Nespresso solve their data issues and deploy their AI strategy with Day 1 ROI.

Simply put, Shelf unlocks AI readiness. We provide the core infrastructure that enables GenAI to be deployed at scale. We help companies deliver more accurate GenAI answers by eliminating bad data in documents and files before they go into an LLM and create bad answers.

Shelf is partnered with Microsoft, Salesforce, Snowflake, Databricks, OpenAI and other big tech players who are bringing GenAI to the enterprise. 

Our mission is to empower humanity with better answers everywhere.

Overview

We are looking for an experienced Engineering Manager to lead three Agile teams (15–20 engineers total). You will own the end-to-end delivery of enterprise knowledge management solutions, AI-powered copilots, and answer assistants. The role blends strategic leadership with hands-on execution in a fast-moving, AI-first SaaS environment.

Key Responsibilities

Autonomous Operation

• Lead a group of teams with minimal oversight.
• Set, facilitate, and achieve quarterly engineering goals and KPIs.
• Make critical decisions on delivery, organization, and process.

Delivery Management

• Partner with Product Management and AI R&D teams to validate the feasibility of roadmaps and identify technical trade-offs.
• Clear delivery roadblocks and manage high-stakes risks.
• Ensure the timely release of knowledge management and AI-assistant features.
• Balance new development with technical debt and customer-support work.

Team Development

• Drive consistent, high team performance; track progress and metrics.
• Hold regular one-on-ones with Tech Leads and coach them; foster Individual Contributors’ day-to-day performance and long-term growth.
• Forecast capacity needs and run hiring with HR; own onboarding and team changes.

Process Innovation & Optimization

• Maintain and improve efficient workflows in Jira, Confluence, DataDog, LinearB, and other systems.
• Refine SDLC, OKRs, KPIs, and other engineering processes.
• Champion AI tools and hands-on workflow automation.

Cross-Functional Collaboration & Communication

• Align with Product Management, QA, and Technical Support on joint initiatives.
• Work with Customer Success and Sales to unblock technical dependencies.
• Report delivery status and engineering performance to leadership; showcase results internally and externally.

Qualifications

• 5+ years as an Engineering Manager in product companies or startups, preferably in SaaS. Experience collaborating with AI R&D teams is a plus.
• Proven track record managing multiple teams (15+ engineers) with complex technical deliverables.
• Strong background in Agile methodologies and process optimization.
• Expert proficiency with project management tools like Jira and Confluence.
• Hands-on process automation with AI adoption in day-to-day workflows. Proficiency in Python and/or JavaScript for data processing is a plus.
• Significant experience with engineering performance measurement and KPIs like DORA.
• Strong track record of collaboration and communication with Product Management, Customer Support, HR, and other departments.
• Excellent people management and coaching skills.
• The ability to operate autonomously at a senior engineering management level.
• Experience presenting to large internal audiences and company leadership.

What Shelf Offers:

• B2B contract.
• Company Stock Options.
• Hardware: MacBook Pro.
• Modern technical stack. Develop open-source software.
• GitHub Copilot subscription.
• Access to Claude Code, OpenAI Codex, TypingMind, and MCP Servers.

Why Shelf:

• GenAI is expected to be a $4 trillion market by 2032, and Shelf is a core infrastructure that enables GenAI to be deployed at scale.
• Our Leadership Team possesses deep knowledge management and AI domain expertise, as well as an enterprise SaaS background, to execute this plan effectively.
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