Jobs at Invisible Technologies

Own a platform domain end to end, defining architecture, roadmap, reliability, security, and cost standards. Build scalable multi-tenant Kubernetes infrastructure, enable self-service deployments, advance agent-native engineering practices, and develop tooling for safe agent execution. Partner with engineering teams to translate infrastructure needs into reusable capabilities, mentor engineers, lead design decisions, and manage on-call and post-incident processes.

Build and operate the company’s platform infrastructure, including Kubernetes, infrastructure as code, CI/CD, identity, secrets, networking, observability, and developer tooling. Responsibilities include operating production services, supporting agent infrastructure, improving alerting, participating in incident response, and creating self-service capabilities. The role requires strong Kubernetes and cloud experience, Terraform, Helm, GitOps, Python, AI coding-agent expertise, sound engineering judgment, written communication, and comfort with ambiguity.

Work directly with clients to scope, prototype, and deploy AI-powered workflows. Build scalable systems using LLMs, embedding and retrieval systems, and backend infrastructure. Translate messy data and operational constraints into production-ready solutions, iterate with stakeholders, and maintain deployed systems (including on-call support).

Lead end-to-end AI solutions as a forward-deployed engineer: scope, design, and deploy ML/LLM systems; partner with clients and stakeholders; build infrastructure, data pipelines, and reusable platform components; mentor engineers; own projects from discovery through production and provide on-call support.

Lead high-impact AI solutions, overseeing architecture and deployment. Partner with stakeholders, coach engineers, and drive project success from inception to launch.