
Staff Software Engineer – AI
Plaid
full-time
Posted on:
Location Type: Hybrid
Location: San Francisco • California • United States
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Salary
💰 $202,800 - $330,000 per year
Job Level
About the role
- Lead projects that enable and scale our business with our largest AI customers and partners, starting with personal finance use cases and expanding into many others
- Develop and evolve the preferred integration pattern for Plaid with AI providers - from API adaptations to building the official Plaid MCP Servers, and beyond
- Redefine how Plaid’s consumer link experience embed into conversational interfaces in the most seamless way
- Architect the trust layer for the future of agentic commerce that will become the industry standard
- Scale and extend our existing successful bets on AI-powered customer experience; examples include making the next step-function improvement in our homegrown customer support agent
Requirements
- Strong SWE fundamentals (system design, APIs, etc.)
- Hands-on experience working with LLMs to build products and shipping them to product with iterating with real user feedback - including but not limited to:
- Prompt engineering
- Fine-tuning
- Retrieval augmented generation (RAG)
- Semantic search - vector database and embedding models
- Agent orchestration framework
- Evaluation and monitoring framework of open-ended tasks
- Streaming and SSE
- Common UX and design patterns for GenAI-powered products
- Strong debugging and monitoring experience for production systems
- Ability to deeply understand customer and user needs through user research and rapid experimentation - be your own technical PM
- Ability to balance divergent thinking (exploring possibilities) with convergent thinking (evaluating feasibility), which is critical for driving 0 ->1 projects
- Extremely curious and passionate about working in GenAI applications space
Benefits
- Comprehensive benefit plan, including medical, dental, vision, and 401(k)
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
system designAPIsprompt engineeringfine-tuningretrieval augmented generationsemantic searchvector databaseembedding modelsagent orchestration frameworkdebugging
Soft skills
user researchrapid experimentationdivergent thinkingconvergent thinkingcustomer understandingcuriositypassion for GenAI applications