Senior Software Engineer - AI Applications

Plaid · Fintech · San Francisco, CA · All Cost Centers

Plaid is building a new AI Applications team to scale their GenAI-powered products and features, focusing on integrating AI into financial services for customer experience, identity verification, and fraud prevention. The role involves full-stack development, architecting GenAI solutions, and rapid experimentation.

What you'd actually do

  1. Build across the stack. Design, develop, and maintain scalable backend services and APIs, as well as intuitive, high-quality frontend applications that bring those systems to life.
  2. Work with other AI engineers, software engineers and machine learning engineers to architect, design and implement GenAI-powered products and features
  3. Collaborate across functions to understand user needs, propose and implement AI-powered solutions where they’re expected to have the highest impact
  4. Design and execute rapid experiments to push the boundaries on potential business impact from emerging AI capabilities, with a focus on minimal viable testing approaches
  5. Balance creative exploration of possibilities with rigorous evaluation of technical feasibility, product potential and business impact

Skills

Required

  • Experience building backend services and working with microservices or service-oriented architectures
  • Strong working knowledge of HTML, CSS, JavaScript, and modern frontend frameworks or libraries, with comfort building user-facing experiences
  • Strong software engineering fundamentals, including system design and API development
  • Hands-on experience building and shipping LLM-powered products, iterating with real user feedback
  • Practical experience with prompt engineering, fine-tuning, RAG, semantic search (vector databases and embeddings), agent orchestration frameworks, and evaluation/monitoring of open-ended tasks
  • Experience building GenAI-powered product experiences, including streaming/SSE and common UX patterns
  • Strong debugging and production monitoring experience
  • Ability to deeply understand customer needs through user research and rapid experimentation; comfortable operating as a technical PM when needed
  • Ability to balance divergent exploration with pragmatic execution, especially in 0 to 1 environments

Nice to have

  • Experience training and deploying ML models in production, including fine-tuning LLMs for domain-specific use cases
  • Comfortable operating in privacy- and PII-sensitive environments, with experience applying appropriate compliance and data protection controls

What the JD emphasized

  • Hands-on experience building and shipping LLM-powered products
  • Practical experience with prompt engineering, fine-tuning, RAG, semantic search (vector databases and embeddings), agent orchestration frameworks, and evaluation/monitoring of open-ended tasks
  • Experience building GenAI-powered product experiences, including streaming/SSE and common UX patterns

Other signals

  • building GenAI-powered products
  • AI agents for customer experience
  • founding members of a newly formed team
  • scaling successful bets