Curium is the enterprise platform for brands to win AI search. Founded by the Princeton team that invented and coined GEO (Generative Engine Optimization), we combine proprietary reinforcement-learning models with a turn-key content optimization platform. Our customers range from household-name consumer brands and a major internet media company to one of the largest US sportsbooks, fast-growing fintechs, and category leaders in energy, education, and real estate. Backed by General Catalyst, the ex-CTO of OpenAI, and the CEO of Intel.

The team

Curium was founded by the Princeton researchers who defined GEO. Co-founder Ameet Deshpande, an Olympiad medalist, went from IIT Madras to a PhD at Princeton. Co-founder Karthik Narasimhan is a Princeton professor whose work includes OpenAI's original GPT paper, ReAct, and SWE-bench, and co-founder Vishvak Murahari came up through Princeton and Google DeepMind. They're joined by engineers from Apple, MIT, and UC Berkeley. We're a small team in San Francisco where everyone writes code, talks to customers, and ships.

What We've Built

Search is moving from ten blue links to one generated answer. Generative engines like ChatGPT, Gemini, Perplexity, and Google AI Overviews retrieve sources, synthesize them, and decide which brands get cited, recommended, and described, and how. That process is a black box. It's non-deterministic, and it shifts with every model update. SEO tools were built to rank pages against a known algorithm, and they have no model of how an LLM reasons about a brand.

We treat GEO as an optimization problem. Curium continuously probes AI engines across the queries that matter to a brand and measures visibility: whether the brand is cited, where it appears in the answer, and how it's described. On top of that, we built proprietary reinforcement learning algorithms that learn which changes to a brand's content, structure, and data actually move those answers, using measured visibility in the engines as the reward signal. The system proposes a change, we ship it, the engines respond, and the models improve with every deployment. This builds on our GEO research, published at KDD 2024.

About The Role

You will be the engineer our largest customers work with every day. You deploy Curium inside enterprise accounts, build the integrations and workflows that make it work for their stack and their brand, and bring what you learn back to the product team. This is a hands-on engineering role, not a solutions sales role. You write and own production software, and you are judged on whether customers actually win in AI search. You will work directly with the founders, and the playbook you build will define how Curium deploys from here.

What You'll Do

• Deploy into enterprise accounts. Own technical onboarding from kickoff to live: CMS, analytics, and data integrations, done right the first time.
• Build what the customer needs. Write the custom integrations, workflows, and tooling that fit Curium to each customer's stack, brand, and approval process.
• Be the technical counterpart. Run the day-to-day with the customer's engineering and marketing teams. Scope the problem, set the plan, and ship.
• Debug the hard cases. Trace a bad outcome back through LLM outputs, data pipelines, and customer systems to the root cause, then fix the system rather than the symptom.
• Turn deployments into product. The best features at Curium start as something an FDE built for one customer. You spot the patterns across accounts and push them into the core platform, which changes where the roadmap goes.

This is a startup. You will go deep on deployments, but you will also be pulled into whatever needs to get done. If you need a clearly scoped job description to be comfortable, this isn't the right fit.

Who You Are

• This role rewards slope over resume. The best FDEs learn fast, think in systems, and are as comfortable with a CMO as they are debugging a pipeline with our engineers. You might come from one of these paths:
• The forward deployed or solutions engineer. You have deployed complex software into enterprises at a high-growth company, sat in front of customers, and owned outcomes. You may not know AI search yet, but you know how to land a hard product in a messy environment.
• The product engineer who wants to be closer to customers. You have shipped production software at a strong product company and you were always the one on customer calls. You want the customer to be your day-to-day counterpart.
• The marketing tech engineer. You have built on CMSs, analytics, or search infrastructure and you know how marketing organizations actually run. You will pick up GEO fast because you already speak the customer's language.

Whatever the path, you are someone who:

• Has shipped production code as an engineer, and writes and owns real software, not just demos or configuration.
• Has worked directly with customers, in forward deployed, solutions engineering, or implementation work where the customer was the day-to-day counterpart.
• Has 5+ years of engineering experience.
• Communicates clearly. Customer engineers and marketing leaders both trust you in the room.
• Is comfortable with ambiguity and owns outcomes end to end.

Nice to have

• Startup experience.
• You have built LLM applications and deployed LLM-powered workflows for customers.

Compensation Range: $180K - $220K

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