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Emergence AI

Principal Engineer (agent framework)

NY, United States

Compensation Range: $250K- 350k

Apply on job-boards.greenhouse.io About employer

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Job details

Pay: Compensation Range: $250K- 350k
Experience: 10+ years of experience building and operating production systems, including technical leadership at the staff or principal level.
Posting language: English
Posted: Nov 6, 2026

Original job description

About Emergence AI

Emergence AI is a frontier agentic AI lab advancing safe, autonomous AI through its pioneering neuroformal architecture. We are building the next generation of enterprise AI: systems capable of understanding complex knowledge, reasoning across information, executing multi-step workflows, and taking action with the verifiability and reliability required for mission-critical environments.

Our Enterprise Agent Platform provides the foundation for building, deploying, and operating AI systems in production - from data connectivity and knowledge management to workflow orchestration, observability, evaluation, and governance. We partner with organizations in semiconductor manufacturing, life sciences, and other data-intensive industries to solve complex challenges that require trusted AI systems capable of operating in real-world environments.

Our team brings experience from leading AI research labs and technology companies, including IBM Research, The Allen Institute for AI, Amazon, and Broadcom. With headquarters in New York and offices across California, Spain, and India, we bring together diverse expertise and perspectives to tackle some of the most challenging problems in enterprise AI.

About the Role

Code is cheap now. Trust isn't. Coding agents can write a feature in minutes, but knowing that it validates its inputs, stays compatible with existing callers, can't double-charge on a retry, doesn't leak a secret into a log, and won't wake someone at 3 a.m. still takes hours of careful review. That review doesn't scale when agents open ten pull requests a day, and it doesn't exist at all when the person directing the agent isn't an engineer.

That second case is the one we care about most. Our customers use AI to build custom software for their businesses, and many of them have never written code. They can't review what the agent produces, and they shouldn't have to. The software still has to be secure, correct, and dependable.

Style guides, templates, and code review can't solve that. Our approach is to move the guarantees out of the code each author writes and into a platform that machines can check. We're building the platform that both our product and our customers' software run on. It packages hard capabilities once, makes every dependency explicit, enforces contracts at every boundary, and refuses to run a system whose requirements it can't meet. Every guarantee it makes is one less thing for a reviewer to check and one more constraint for builders to live with, and drawing that line well is the central design problem. The platform is built on a few principles that are easy to state and hard to get right: every system declares what it is allowed to do, the secure path is the default path, behavior is the same from development to production, the platform evolves without breaking what depends on it, and agents are first-class users.

We're hiring a Principal Engineer to shape where the platform goes, build it, and grow the team around it. In your first few months, you'll learn the platform's model deeply, challenge the parts that are wrong, ship meaningful improvements to its core, and lay out a vision for where it goes next that the team and leadership are behind. Within your first year, our engineers and our customers will both be building real software on the platform with AI, that software will hold up in production, and engineers you've mentored will lead major parts of the platform.

New York City is preferred for this role (hybrid). We're also open to remote candidates anywhere in the United States.

You'll

Set the platform's long-term technical vision and make the case for it so clearly that engineers, product leaders, and executives understand where it's going and why.
Lead technical direction for the platform's core abstractions, from design proposal to shipped code, with agents doing most of the typing.
Build platform capabilities such as data, messaging, background work, identity and access, AI model access, and external integrations, each with clearly stated guarantees.
Own the security model: trust boundaries, isolation, secrets, authentication and authorization, and exposure to the internet.
Shape the agent experience: the tooling, feedback loops, documentation, and constraints that keep agent-generated software correct for our engineers and our customers.
Own the path to production: deployment, environment configuration, observability, and health.
Partner with the product and AI teams building the customer experience on top of the platform.
Mentor engineers at every level, from new hires to staff engineers, in system design, platform thinking, and building with agents.

You'll Have

10+ years of experience building and operating production systems, including technical leadership at the staff or principal level.
Deep platform engineering experience: you've built frameworks, runtimes, or infrastructure that other people build on, and you've lived with the consequences of your abstractions for years.
Strong system design skills and fluency in distributed systems, including failure modes, consistency, idempotency, messaging, and API evolution, and an eye for the one-way doors in a design.
A security mindset: you think in trust boundaries and capabilities, and you'd rather make a mistake impossible than document how to avoid it.
Daily, hands-on experience building with coding agents. You've seen them do excellent work and fail in subtle ways, and you have a point of view on how to get the first without the second.
The ability to communicate ambitious ideas clearly: describing where a platform needs to be in a few years, explaining why, and turning that into steps a team can ship this quarter. You write design documents people want to read and can make the case to an engineer, a product leader, or an executive.
A track record of helping engineers grow into senior and staff roles through design reviews, pairing, and candid written feedback.
A highly collaborative style: you invite critique, change your mind when the evidence says so, and build agreement without slowing the team down.
A fast-moving, self-driven approach: you don't need a roadmap handed to you. You find the most important problem, make a call, ship it, and learn from what happens.

Emergence AI offers competitive compensation.

Comprehensive health benefits including medical, dental and vision.
401(k) with company match.
Flexible PTO and company holidays.
Flexible hybrid/remote work environment.
The opportunity to work at the forefront of technological advancement.

Compensation Range: $250K- 350k

Emergence AI is an equal opportunity employer committed to building an inclusive workplace where people with diverse backgrounds, experiences, and perspectives can do their best work. We believe building trustworthy AI requires diverse ways of thinking, and we're committed to creating an environment where everyone can thrive.

If you're excited about this opportunity but don't meet every qualification, we encourage you to apply. We value curiosity, ownership, and the ability to learn just as much as matching every item on a job description.

Apply on job-boards.greenhouse.io About employer

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Jobs in the United States