Full Stack Software Engineer - AI Applications

Ford Ford · Auto · Long Beach, CA +2 · Enterprise Technology

This role focuses on building and shipping AI-powered applications and agents, specifically using AI for development tasks like orchestration and code generation. The engineer will design, deploy, and operate cloud-native systems on GCP, integrating various enterprise platforms and automating manual processes. A strong emphasis is placed on using AI as a primary work method, with the engineer directing, reviewing, and hardening AI-generated output.

What you'd actually do

  1. Orchestrate agents to build. Use AI as your default way of working — agents do the heavy lifting, you direct, review, and harden. You set the bar for how the team builds with AI.
  2. Build the AI use cases. Design and ship AI-powered applications and agents — RAG pipelines, LLM integrations, agentic workflows. Understand what's happening under the hood and make it work in production, at scale.
  3. Ship cloud-native systems on GCP. Design, deploy, operate. You own the architecture, the infrastructure-as-code, and the CI/CD pipeline. No throwing code over the wall.
  4. Connect systems that don't want to be connected. Build the integration layer across enterprise SaaS platforms. Expect messy APIs, legacy constraints, and creative problem-solving.
  5. Automate what shouldn't be manual. If a human repeats it, you write the code — or point an agent at it — to stop it.
  6. Make other engineers faster. Build the tools, agent workflows, and guardrails that remove friction. Developer productivity is a multiplier.

Skills

Required

  • Python
  • JavaScript / TypeScript
  • AI engineering (LLMs, embeddings, vector stores, RAG)
  • GCP
  • Databases (relational and NoSQL)
  • APIs & microservices
  • Git, IaC & CI/CD
  • BS in Computer Science, Electrical Engineering, or a related field
  • 2+ years building and deploying full-stack applications in production
  • 2+ years on cloud-native platforms (GCP preferred)
  • Demonstrable experience building AI agents or applications

Nice to have

  • Frontend strength is a big plus
  • Bonus for fine-tuning or eval work

What the JD emphasized

  • agent orchestrator
  • building AI applications and agents
  • production at scale
  • security, compliance, legacy systems

Other signals

  • building AI applications and agents
  • orchestrating agents
  • production at scale