Senior Software Engineer, Applied AI (fullstack)

Okta Okta · Enterprise · San Francisco, CA · BT Engineering Services-779

Senior Software Engineer, Applied AI (Fullstack) at Okta, focusing on building GenAI-powered applications, including web UIs and backend services. The role involves integrating LLMs, developing RAG pipelines, and creating reusable frontend components for internal use. Requires strong full-stack skills with an emphasis on AI integration and user-facing interfaces.

What you'd actually do

  1. Design and build end-to-end GenAI-powered applications, including web-based UIs, API services, and backend orchestration.
  2. Implement and integrate LLM-based experiences using frameworks like LangChain, LlamaIndex, and tools like OpenAI, Claude, or Gemini.
  3. Define, implement, and champion operational excellence standards (SLOs, observability, incident response frameworks) for all services deployed.
  4. Develop responsive, accessible, and modern frontend interfaces using frameworks like React or Vue — with a focus on usability, performance, and trust in AI outputs.
  5. Build and maintain a library of reusable frontend components and hooks that allow other business delivery teams to easily "drop in" GenAI capabilities into their own applications.

Skills

Required

  • Python
  • AWS
  • Docker
  • RESTful APIs
  • React
  • TypeScript
  • Vue
  • LLM integration
  • RAG pipelines
  • prompt engineering
  • LangChain
  • LlamaIndex
  • distributed systems
  • APIs
  • microservices
  • container orchestration (ECS/EKS)
  • cloud platforms (AWS/GCP/Azure)
  • secure coding
  • authentication/authorization
  • internal data governance

Nice to have

  • design systems
  • AI evaluation tooling
  • real-time application performance monitoring

What the JD emphasized

  • building AI/ML-driven applications
  • frontend technologies
  • LLM integration
  • building intuitive, performant UIs

Other signals

  • integrating GenAI and intelligent automation into workflows
  • virtual agents, AI copilots, internal RAG services
  • building user-facing and backend systems that leverage GenAI