Embedded Intelligence Operator

Embedded Intelligence Operator

Location:

New York City (on-site)

About the Client

We are a venture-backed technology company helping large enterprises detect and prevent sophisticated fraud at scale. Our software combines open-source intelligence, network analysis, and machine learning to surface what our customers cannot easily find on their own: individuals whose online activity contradicts what they have reported, and the organized networks behind coordinated fraud schemes.

We have product-market fit and happy enterprise customers, and we are growing. Every new customer we sign is paying us enterprise money and expects enterprise results. That is where you come in.

Client name disclosed upon mutual interest.

About the Role

Most companies would call this a Forward Deployed Engineer. We call it an Embedded Intelligence Operator, because the job is less about shipping code and more about being the person inside our customers' world who makes the product work for them.

You will be assigned to enterprise insurance carriers and become their go-to person at our company. On Monday you might walk a Special Investigations Unit director through how we mapped a fraud ring on their book. On Tuesday you might be sitting next to someone on their claims or IT team, figuring out why their data isn't flowing the way it should. On Wednesday you are back with our engineers, translating what you heard into something they can build.

You champion the product to the customer, and you champion the customer to the product. You take the initiative to keep the account happy before anyone has to ask.

What This Role Is Not

Not a pure software engineering role. You will build things, but the customer comes first.

Not a sales role. You will help accounts grow, but you are not carrying a quota.

Not remote.

Responsibilities

• Own the day-to-day relationship with a set of enterprise insurance customers after the contract is signed: onboarding, training, check-ins, and the hard conversations
• Demo and explain our platform and our investigative outputs to users ranging from frontline adjusters to SIU leadership
• Get your hands into customer data: pull it, query it, clean it, and figure out what's broken when something looks off
• Filter customer feedback into clear, prioritized input for our engineering team, and tell customers honestly what's coming and what isn't
• Use AI tools, Claude especially, to build the scripts, analyses, and small workflows that save you and your customers time
• Spot expansion opportunities and problems early, and raise them before they become surprises
• Write the playbooks so the next person in this seat starts faster than you did

Requirements

• Must-Haves
• Two to three years of experience after undergrad. This should be your second job. You have learned how a real organization works and you are ready for more ownership.
• Dangerous with Claude. You use AI tools daily, not as a novelty but as how you get work done. You can show us something you built or automated with them.
• You know how a database works. Tables, joins, keys, why a query returns the wrong number. Comfortable writing basic SQL or learning it fast. You do not need to be a software engineer.
• Good in a room. You can brief a senior executive in the morning and work through a data problem over an analyst's shoulder in the afternoon, and both of them want you back.
• Initiative. Nobody has to tell you a customer is unhappy. You noticed first and already have a plan.
• Low ego, easy to work with. Small team, high trust. We care a lot about how you show up.
• On-site in our NYC office. Being in the room with our engineers and leadership is how this role works.
• Nice-to-Haves
• Forward-deployed, deployment strategist, solutions engineering, implementation, or technical customer success experience at a data or software company
• Exposure to insurance, claims, fraud, trust and safety, investigations, or intelligence work
• Military service, especially in intelligence, communications, or other roles where you translated between operators and technical teams
• Python, data visualization, or other light technical skills beyond SQL
• An MBA is not needed.
• Why This Role
• Real ownership of enterprise customer relationships much earlier than you would get at a big company
• A direct line to the engineers and leadership who build the product, with real influence on what gets built
• Work that catches people committing fraud, which is more satisfying than it sounds
• A role that grows as we grow
• A fast process: about two interviews, then a decision
• How to Apply
• Send a one-page resume and a short note on something you built or figured out with AI tools that you are proud of.