AI
AI Engineer
- Experience6 - 12 years — in backend/AI engineering, building and deploying LLM systems in production
- Compensation$200K - $350K
- Salary detail$200,000 – $350,000 base salary depending on experience
- EquityCompetitive equity
- VisaNone, Visa transfers
- Work policyPreferably in New York, NY (WeWork initially, permanent office space being finalized) but open to anywhere in US
- LocationNew York, San Francisco, South Bay Area, Los Angeles, Boston, Seattle, Texas, Chicago, Washington DC, Denver, Florida, Minnesota, Sacramento
- TypeFull-time
- Tech stackPython, LLMs, GenAI, RAG, Kubernetes, CI/CD, REST APIs, Cloud (AWS/GCP/Azure)
The Opportunity
We are looking for an AI Engineer with 5–10+ years of experience to own the technical build-out of a custom AI/LLM platform for one of the top 5 banks in the US. You'll be part of a tight-knit, execution-focused team at a Series A startup that ships real AI in production — not papers, not prototypes. This is a high-ownership role where you'll work closely with both the core engineering team and a marquee enterprise customer to make things work end-to-end.
What You'll Be Doing
- Fork and customize the core AI/LLM platform for a top-5 bank's environment, owning the full technical build from architecture to deployment
- Collaborate daily with the Israel-based engineering team to merge customer-specific work with the main product repo
- Own production deployments, integrations, and reliability of AI/LLM systems in a regulated enterprise environment
- Serve as the go-to technical point of contact for the bank's engineering stakeholders (~20% customer-facing)
- Troubleshoot complex production issues and drive solutions end-to-end with high independence
About the Company
The company is a stealth-mode AI startup building a work model for regulated enterprises. The company develops an ambient discovery platform that observes everything an employee does on their computer — watching screen activity, mouse movements, and keyboard inputs — then augments and enhances their workflows using custom AI models deployed end-to-end within the customer's environment. Founded by repeat entrepreneurs with deep roots in Israeli Defense Force intelligence and AI research, the company is on its second venture together. The company focuses on large regulated enterprises, primarily in finance — serving top-tier banks and financial institutions with production-grade, self-hosted AI solutions. The company operates as an applied research lab with an execution-first mindset. The team has academic AI backgrounds but prioritizes shipping production systems, deploying custom models, and delivering real customer value over publishing papers. The company buys its own GPUs rather than renting, self-hosts models, and maintains full control of its AI infrastructure stack. Backed by Insight Partners and other top-tier investors with tens of millions in funding, the company is rapidly scaling — currently around 25 people with plans to grow to approximately 70 by end of year. The company has already closed seven-figure deals with top-5 US banks and is deploying its platform across multiple enterprise customers.
Founded in 2022, team size around 25 employees, $23M in total funding raised.
About the Team
The company is built on a tight-knit, battle-tested core team. Half of the R&D team has worked together before — both at the founders' previous successful startup and in the Israeli Defense Force intelligence section. This is a team that's been through it together, knows how to execute, and is running the playbook for the second time. Working at the company means: No politics, no bullshit — a coherent team with deep trust built over years of working together Execution over academia — the team has strong research backgrounds but cares about getting models into production and solving real customer problems High ownership — everyone reports directly to the CEO, there are no layers of management, and engineers own their work end-to-end Builder culture — the company values AI builders who create the right architectures, work on cutting-edge problems, care about customers, and get things working in production
The team is split between Tel Aviv and New York, with the New York office currently being established. The culture is fast-paced, startup-native, and deeply technical — ideal for engineers who want to ship production AI systems for high-profile enterprise customers.
The Product
The company builds a custom AI work model platform for regulated enterprises. The platform performs ambient discovery on employee computer activity — observing screen content, mouse movements, and keyboard inputs — to understand and augment how employees work. Key aspects of the product: Ambient Discovery: The platform watches and understands everything happening on an employee's workstation to build contextual intelligence about workflows Custom Models: The company develops and deploys custom AI/LLM models tailored to each enterprise customer's specific environment and needs End-to-End On-Premise Deployment: Models are deployed entirely within the customer's infrastructure — critical for regulated industries like banking where data cannot leave the environment Self-Hosted Infrastructure: The company owns its own GPU stack and self-hosts all models, maintaining full control over the AI pipeline from training to production
The platform is designed for large financial institutions and regulated enterprises that require the highest levels of data security, compliance, and customization. Each deployment is a custom fork of the core platform, tailored to the specific customer's environment and requirements.
Application Questions
- Describe your experience working directly with enterprise customers or their technical stakeholders — particularly in banking or regulated industries.
- What is your experience in building and deploying LLM/AI systems in production environments?