Software Engineer, Generative AI

Writer Writer · AI Frontier · San Francisco, CA · Engineering, product & design

Software Engineer, Generative AI role focused on building secure, scalable generative AI services and applications, optimizing APIs and microservices for LLMs and agentic workflows, and owning system design and architecture. The role involves integrating AI models, developing user interfaces, and partnering with DevOps for CI/CD and monitoring. Requires strong Python, generative AI, LLM, vector database, and microservices experience, with exposure to cloud platforms and enterprise security.

What you'd actually do

  1. Design and develop robust, secure, and scalable generative AI services and applications using Python and modern frameworks to drive enterprise-wide transformation
  2. Build and optimize high-performance, low-latency APIs and microservices to integrate advanced AI models and sophisticated agentic workflows into our core platform
  3. Act as a whole-systems thinker by making meaningful system design decisions and owning the architecture of core platform components from initial proposal through production deployment
  4. Implement and maintain responsive user interfaces using technologies like React and TypeScript to deliver intuitive user experiences and bridge the gap between backend services and frontend enablement
  5. Drive proactivity without red tape by clearly communicating changes, plans, and proposals to cross-functional teams and collaborating closely with product managers, data scientists, and DevOps engineers

Skills

Required

  • 3-5+ years of hands-on experience as a software engineer with a strong emphasis on Python development in production environments
  • Proven expertise in building and deploying generative AI applications, leveraging LLMs, vector databases like Pinecone, Weaviate, or pgvector, and modern open-source agentic frameworks
  • Practical experience with microservices architecture, RESTful APIs, cloud platforms such as AWS, GCP, or Azure, and containerization with Docker and Kubernetes
  • Solid grasp of modern web technologies including FastAPI, Asyncio, database systems like PostgreSQL, and hands-on experience leveraging AI developer tooling like Claude, Cursor, or GitHub Copilot to accelerate your engineering workflows
  • Exposure to enterprise architecture including practical experience implementing IAM, SSO, SAML, OAuth, OIDC, RBAC, robust security best practices, or building services for enterprise administration and billing systems

Nice to have

  • Connect mindset that thrives in collaborative settings where you actively engage with cross-functional teams and mentor other engineers
  • Challenge spirit that drives you to tackle complex technical hurdles and proactively suggest innovative improvements
  • Own attitude where you take full accountability for delivering high-quality, resilient, and scalable code from conception to production

What the JD emphasized

  • building and deploying generative AI applications
  • leveraging LLMs, vector databases
  • modern open-source agentic frameworks
  • low-latency APIs
  • agentic workflows
  • whole-systems thinker
  • owning the architecture
  • proposal through production deployment
  • Python development in production environments
  • cloud platforms
  • containerization
  • FastAPI
  • Asyncio
  • enterprise architecture
  • robust security best practices
  • building services for enterprise administration and billing systems

Other signals

  • building and deploying generative AI applications
  • leveraging LLMs, vector databases
  • modern open-source agentic frameworks
  • building the secure, scalable foundation that allows our generative AI solutions to thrive