Senior AI-Native Fullstack Engineer; m​/f​/d; DevOps

Job Description

We are looking for a Senior AI‑Native Fullstack Engineer with a Dev Ops focus to support multiple engineering projects across AI‑powered applications, SaaS platforms, and cloud‑native solutions. This is not a traditional Dev Ops‑only role. The role combines application engineering with infrastructure ownership: building services, APIs, automation and internal tools, while also running cloud infrastructure, deployments, observability and production operations.

The ideal profile is a strong full‑stack or backend engineer, preferably Type Script‑heavy, with hands‑on depth in AWS, Infrastructure as Code, containers, networking, permissions, secrets and observability. With modern AI and LLM tooling, repetitive engineering, infrastructure, debugging and automation work can be accelerated dramatically. We expect someone who uses AI‑native workflows to investigate in parallel, generate and validate infrastructure changes, and support teams with high‑quality execution.

• Builds application software and owns the infrastructure behind it
• Uses AI as a default development and troubleshooting workflow
• Cares about reliability, security, automation, observability and maintainability
• Chooses simple solutions, owns outcomes, and verifies aggressively

• Full‑stack Engineering:
  Build services, APIs, scripts, automation, internal tools and lightweight frontend functionality where useful, mainly in Type Script
• Infrastructure & Cloud Setup:
  Use IaC, ideally AWS CDK, to build pragmatic cloud patterns across containers, databases, queues, storage, networking, DNS, secrets and runtime configuration
• ECS Fargate Operations:
  Deploy and troubleshoot ECS Fargate workloads, including task definitions, services, load balancers, IAM roles, logs, scaling and deployment behavior
• Security, Observability & Troubleshooting:
  Handle IAM, least privilege, secrets, logs, metrics, alarms, failed deployments, configuration issues, networking problems and runtime incidents

• Hands‑on use of Claude Code, Codex or similar advanced AI tools;
  Copilot‑style autocomplete is not enough
• Uses agents for development, infrastructure changes, debugging and operational investigation, while strongly reviewing and testing AI‑generated code, scripts and configuration

• Strong fullstack or backend engineering experience, especially with Type Script; able to build production services, APIs, scripts, tools and automation
• Comfortable across application code, infrastructure code, deployments and runtime systems, from problem clarification to production rollout

• Strong IaC and AWS or similar cloud experience, ideally AWS CDK with Type Script, across containers, ECS Fargate, networking, IAM, secrets, DNS, storage, databases, queues and runtime configuration
• Strong observability, security and delivery judgment: logs, metrics, traces, dashboards, alarms, least privilege, deployment safety, pipeline permissions and safe developer access
• Pragmatic production debugger with good judgment on scalability, availability, cost, security, operational trade‑offs and clear English communication

You may be a good fit if you are a fullstack/backend or Type Script engineer with strong AWS, IaC and Dev Ops experience; a Dev Ops/platform or SRE‑minded engineer with real software engineering depth; or an AI‑native builder using LLMs and agents daily for real development and infrastructure work.

This role is probably not the right fit if you are mainly an infrastructure admin who avoids coding, a pipeline‑only Dev Ops profile, a pure application developer with no cloud ownership, someone who only wants predefined tickets, or someone…