Head of Engineering - AI Data Platform, .NET

Title: Head of Engineering (Senior Engineering Manager/Director level)Location: Remote in U.S.; ideally Seattle, SF Bay Area, Orange County/LA, NYC, or Boston

Comp:$200K–$265K base + equityTL;DR:

We’re hiring a Senior Engineering Manager for a profitable, fast-growing (50% YoY) Series B SaaS company building an AI-driven, cloud-native data modeling platform used by more than 400K global enterprise users. You’ll lead and technically guide a 12-person engineering team to restore and scale execution rigor, improve SDLC performance, and guide architectural decisions for their next phase of AI and transformation-modeling expansion. $200-265K base + equity

About the Client Company:

Our client builds an AI-first, cloud-based enterprise data modeling platform that helps distributed data teams design, visualize, and manage their ecosystems without writing code. Their users include global data-driven organizations and Fortune 500 companies that rely on the platform to bridge relational and transformational modeling in one place.

More than 400,000 global users currently rely on their NCLC tech. They are profitable, technically Series B, and scaling at more than 50% YoY. They’re entering a major product evolution cycle focused on AI, end-to-end modeling, and significant architectural upgrades.

The Opportunity:

We’re hiring a Senior Engineering Manager who blends strong technical depth with disciplined, business-aligned leadership. This is a hands-on strategic role for someone who has shipped real code within the past three years, understands modern cloud and AI-inflected architectures, and knows how to turn engineering teams into reliable, accountable, high-output organizations.

You’ll manage a team of roughly ten engineers plus an architect and DevOps partner, working closely with Product, Operations, and the Executive team to rebuild structure, improve velocity, and strengthen the engineering culture. This is not a pure people-manager role. You’re expected to bring technical credibility, architectural insight, and the judgment to balance speed with quality… prioritizing productivity over perfection.

Core Responsibilities:

• Lead and mentor a mid-sized engineering team, setting standards for planning, estimation, quality, and delivery.
• Bring rigor back into the SDLC: sprint hygiene, capacity planning, defect tracking, and engineering metrics that matter.
• Partner with Product to translate themes and OKRs into technical plans that are realistic, achievable, and aligned with customer needs.
• Maintain hands-on technical fluency so you can engage deeply in architecture reviews, unblock engineers, and make high-quality decisions with context.
• Ensure engineering efforts are connected to business outcomes, not just ticket flow.
• Support and scale the offshore team, creating consistency in quality, communication, and ownership.
• Help drive AI-enabled product initiatives from a technical and execution standpoint.

Qualifications:

• 10+ years of overall software engineering experience with at least 3 years leading teams (Senior Manager through Director track).
• Recent (within the past few years) hands-on experience: you’ve been involved in coding, reviewing architecture, or shipping features using C#.NET Stack.
• Strong background in C#/.NET and cloud infrastructure (AWS, Azure, or GCP).
• Experience scaling teams in a Series A–C SaaS environment (~$10M – $25M ARR up to $80M).
• Proven success managing distributed or offshore teams.
• Working knowledge of modern AI or ML product integration for enterprise applications.
• Strong communicator who connects engineering decisions to business outcomes.
• Personality fit: low ego, collaborative, steady under pressure, knows how to create clarity and momentum. Pragmatic, data-informed, and motivated by delivery.

Why This Role Stands Out:

• Join a profitable, high-growth SaaS company transforming enterprise data modeling.
• Help shape the engineering organization during a pivotal AI-driven expansion phase.
• Enjoy the autonomy, flexibility, and impact of a fully remote, product-led environment.
• Build a high-performing org that directly influences how modern enterprises manage data integrity, collaboration, and productivity.