Full Stack Software Engineer - AI Applications

Ford Ford · Auto · Palo Alto, CA +1 · Enterprise Technology

Full Stack Software Engineer focused on building and orchestrating AI agents and applications within an enterprise context, emphasizing cloud-native development on GCP and integrating various systems. The role involves designing, deploying, and operating AI-powered applications, RAG pipelines, and LLM integrations, with a focus on developer productivity and automation.

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
  • React
  • Node.js
  • LLMs
  • embeddings
  • vector stores
  • RAG
  • building agents
  • evaluation pipelines
  • GCP
  • Cloud Run
  • Cloud Functions
  • GKE
  • BigQuery
  • Cloud Storage
  • databases
  • APIs & microservices
  • RESTful services
  • Git
  • IaC
  • CI/CD
  • Terraform
  • Cloud Build
  • BS in Computer Science, Electrical Engineering, or related field
  • 2+ years building and deploying full-stack applications in production
  • 2+ years on cloud-native platforms (GCP preferred)

Nice to have

  • Front-end strength
  • fine-tuning
  • eval work
  • MS in Computer Science, Electrical Engineering, or related field

What the JD emphasized

  • agent orchestrator
  • AI agents
  • agentic workflows
  • production, at scale
  • cloud-native systems on GCP
  • enterprise SaaS platforms
  • AI agents or applications

Other signals

  • AI agents
  • agent orchestration
  • LLM integrations
  • production scale
  • cloud-native systems
  • enterprise SaaS integration