Staff Software Engineer - AI Applications

Plaid · Fintech · San Francisco, CA · Engineering

Staff Software Engineer role focused on building and scaling AI applications within Plaid's FinTech ecosystem. The role involves developing integration patterns for AI providers, enhancing conversational AI interfaces, architecting trust layers for agentic commerce, and extending AI-powered customer experience agents. This includes working with multi-turn, multi-agent systems, RLHF, and customer-specific memory, as well as expanding agents to support product recommendation, onboarding, and upselling.

What you'd actually do

  1. 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
  • Hands-on experience working with LLMs to build products and shipping them to product with iterating with real user feedback
  • Prompt engineering
  • Fine-tuning
  • Retrieval augmented generation (RAG)
  • Semantic search - vector database and embedding models
  • Agent orchestration framework

Nice to have

  • multi-turn and multi-agent system
  • offline evaluation for complex multi-turn open-ended tasks
  • Human-In-The-Loop - Reinforcement Learning (RLHF)
  • customer-specific long-term memory
  • product recommendation
  • customer onboarding
  • risk diligence
  • customer activation
  • upselling and cross-selling

What the JD emphasized

  • Hands-on experience working with LLMs to build products and shipping them to product with iterating with real user feedback

Other signals

  • building AI agents for customer experience
  • consolidating and rapidly scaling our successful bets
  • grow with the team in our quest to accelerate Plaid’s transformation into an AI-first company