AI Engineer

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.

• 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

• Python
• Large Language Models (LLMs)
• Generative AI
• Retrieval‑Augmented Generation (RAG)
• Agentic AI Systems
• Kubernetes
• CI/CD Pipelines
• REST APIs
• AWS, GCP, or Azure

• 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

• 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

• 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

• Your experience is primarily research-focused with limited production deployment ownership
• You’ve mainly worked as a Data Scientist, Data Engineer, ML Researcher, or Dev Ops/SRE without significant software engineering responsibility
• You’re looking for a highly structured large‑enterprise environment rather than a startup setting

• 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.