Job Description

Role: Principal Engineer ( Net)

The Role:

We are hiring a Principal Engineer as a hands-on technical leader. You will operate as a forward-deployed engineer, embedding directly with portfolio companies and product teams to build new products from zero-to-one, rewrite existing products from the ground up using AI-native approaches, and take on high-leverage special projects for Venture AI Labs. This is not a role where you will hand off designs and watch others build. You will architect, write code, review code, and set the technical bar for the teams around you.

What You'll Do

Your work will span four distinct but connected tracks:

• Full AI-native product rewrites. Take an existing product and rebuild it entirely using an AI-native approach — rethinking architecture, data model, UX, and delivery pipeline rather than porting the old system one-for-one. You will prove out what 'AI-first from the ground up' actually looks like in production.
• Rapid modernization for portfolio companies. Parachute into portfolio companies to accelerate the build of a new product inside one of Embrace's six regulated industry verticals. You will bring AI-first engineering practices, modern architecture, and senior judgment to teams that need to ship quickly without compromising on the compliance and reliability these markets demand.
• Net-new products for regulated markets. Build entirely new products aimed at these same regulated verticals — not by digitizing existing workflows, but by rethinking the workflows themselves now that AI makes previously impossible experiences possible.
• Venture AI Labs special projects. Take on high-impact, high-ambiguity initiatives out of Venture AI Labs — applied research, prototypes, and strategic bets that the CTO and CEO need moved forward by a senior engineer who can operate independently.

Across all of this, you will also:

• Lead AI-first development, where the majority of code is produced through leading AI coding tools (Claude Code, Codex, GitHub Copilot, Cursor, JetBrains AI). You will set the patterns for how humans and AI agents collaborate to ship production software safely and quickly.
• Own architecture and solutioning end-to-end: system design, technology selection, data models, API contracts, deployment topology, and non-functional requirements (performance, security, observability, cost) — with extra care given the regulated environments we operate in.
• Drive code review standards and raise the quality bar across teams, for both human-written and AI-generated code. Establish review practices, automated guardrails, and evaluation approaches specific to AI-assisted workflows.
• Partner with the CTO, Engineering Leadership on technical strategy across the portfolio, and with the CEO on initiatives that connect engineering directly to business outcomes.
• Mentor senior and lead engineers across the group; model what great looks like in an AI-first, polyglot environment.

Requirements

What We're Looking For

• 6–12 months of demonstrable AI-first development experience, where the majority of your code has been written through Claude Code, Codex, GitHub Copilot, Cursor, or JetBrains AI. You have strong opinions on prompting, agent orchestration, context management, review workflows, and when to trust (or distrust) AI output.
• Deep expertise in .NET / C# as a primary stack, with Python as strong supporting technology. Being a polyglot is a meaningful plus — we value engineers who reach for the right tool.
• A track record of architecting and shipping non-trivial systems: distributed services, data-intensive applications, cloud-native deployments, and integrations.
• Experience rewriting, re-platforming, or significantly modernizing existing products — you know the difference between a port, a refactor, and a rethink.
• Strong fundamentals in software design, testing strategy, CI/CD, observability, and secure-by-default engineering. Comfort operating in regulated environments is a plus.
• Experience as a forward-deployed or embedded engineer — comfortable with ambiguity, direct customer contact, and shifting context across products and teams.
• Excellent communication — able to align engineers, product, and executives around a technical direction.
• Bias to action, high ownership, and the judgment to know when to move fast and when to slow down.

Nice to Have

• Experience leading or managing a pod in a high-velocity R&D group, innovation lab, incubator, fast-moving startup, or an equivalent skunkworks-style team inside a larger enterprise is a meaningful differentiator. We want engineers who know how to run small, focused teams that ship.
• Experience building with LLMs directly — RAG, evals, agent frameworks, tool use, fine-tuning.
• Prior work inside regulated industries (financial services, healthcare, legal, insurance, compliance-driven SaaS, etc.).
• Open-source contributions or public technical writing on AI-assisted development.

Additional Information

All your information will be kept confidential according to EEO guidelines.