AI Engineer

Location: US East Coast (Remote)

Experience: 6-12 Years We’re partnering with a fast-growing venture-backed AI startup that’s building and deploying production-grade AI solutions for large enterprise customers. They are looking for an experienced AI Engineer to lead the implementation and deployment of a custom AI platform for a major financial services organization. This is a hands‑on, high‑impact role for someone who thrives in startup environments, enjoys solving complex technical challenges, and has experience taking AI products from concept to production.

What You’ll Do: Lead the end-to-end implementation of a customized AI/LLM platform within a large enterprise environment Design, build, and deploy production‑grade AI applications and services Collaborate closely with a globally distributed engineering team to integrate customer‑specific functionality into the core platform Own system reliability, performance, and scalability across AI‑powered workflows Act as a technical partner to customer engineering and technology stakeholders Troubleshoot complex production issues and drive solutions independently Contribute to architecture decisions, platform evolution, and engineering best practices Tech Stack Python Large Language Models (LLMs) Generative AI Retrieval‑Augmented Generation (RAG) Agentic AI Systems Kubernetes CI/CD Pipelines REST APIs AWS, GCP, or Azure

Required Experience: 6-12 years of software engineering experience, with a strong focus on backend or AI engineering Proven experience building and deploying LLM‑based or agentic AI applications in production Strong Python development skills and experience delivering customer‑facing product features end-to-end Deep understanding of software architecture, distributed systems, and system design Experience working directly with enterprise customers and shipping production software Bachelor’s degree in Computer Science or a related technical field

Ideal Background: Currently or recently working at a high‑growth, venture‑backed AI startup (Series A-D) Experience building AI products used by external customers rather than internal‑only tools Comfortable operating in fast‑paced, ownership‑driven environments Strong communication skills and ability to work directly with technical stakeholders

Nice to Have: Experience with cloud infrastructure (AWS, GCP, or Azure) Kubernetes and containerized deployments CI/CD automation and observability tooling Experience operating AI systems in regulated or enterprise environments Not the Right Fit If Your experience is primarily research-focused with limited production deployment ownership You’ve mainly worked as a Data Scientist, Data Engineer, ML Researcher, or DevOps/SRE without significant software engineering responsibility You’re looking for a highly structured large‑enterprise environment rather than a startup setting

Why Join? Build real AI products being used in production today Work directly with enterprise customers solving high‑value problems High ownership and autonomy from day one Opportunity to shape the future of an AI platform at a rapidly growing startup Collaborative, execution‑focused engineering culture Interested? We’d love to hear from engineers who have successfully taken LLM‑powered products from prototype to production and enjoy owning technical outcomes end-to-end.