AI Tooling Engineer

Whatnot

$130K — $180K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in software engineering with a focus on AI tools
  • Proficient with AI technologies and frameworks including LLMs and systems integration
  • Strong experience in building and deploying full-stack applications
  • Ability to translate complex problems into practical software solutions
  • Demonstrated experience in mentoring and elevating team capabilities
  • Excellent communication skills to collaborate with both technical and non-technical stakeholders

Responsibilities

  • Own end-to-end ambiguous AI projects, identifying high-leverage problems and driving solutions from prototyping to production
  • Rapidly build and ship internal applications and prototypes, iterating based on user feedback
  • Define reusable patterns and shared infrastructure to streamline development across the organization
  • Embed within cross-functional teams to collaboratively identify and solve key operational issues
  • Integrate AI tools with existing systems and data sources via APIs and connectors
  • Develop and implement AI workflows that incorporate Whatnot’s data while ensuring compliance
  • Package successful initiatives into reusable skills and playbooks to enhance organizational efficiency

Benefits

  • Flexible time off policy and company-wide holidays including seasonal breaks
  • Health insurance options including medical, dental, and vision coverage
  • Support for remote work including office setup and monthly allowances for communication expenses
  • Wellness and childcare allowances, plus family planning benefits
  • Retirement plans with employer matching and international pension options
  • Monthly allowance for hands-on experience with the product through 'dogfooding'
  • Generous paid parental leave policy with a gradual return to work program
Full Job Description
The Role

We're looking for a Senior AI Engineer to build the internal tools, prototypes, and business workflows that put AI into the hands of every team at Whatnot-and to set the patterns the rest of the company builds on. You'll own ambiguous, cross-org bets end-to-end: finding real problems, shipping working software fast, hardening what works, and scaling how Whatnot gets value out of AI.

This is a high-velocity, high-judgment builder role. You've shipped a lot of apps and prototypes-you're someone who can sit with a CX lead or an ops manager, understand their workflow in an afternoon, and have a working prototype in their hands by the end of the week. But you also operate above any single project: you decide where the leverage is, define the reusable patterns and infrastructure others adopt, and raise the bar for how the whole org builds with AI. You move fluidly across the stack (frontend, backend, data, and the AI layer) and are deeply fluent in the current generation of AI tools and the production patterns around them-prompt engineering, RAG, MCP, agents, and evals.

This is not a model-training or research role. You won't be training models-you'll be building the tools, workflows, and integrations that make off-the-shelf AI dependable and useful inside Whatnot's systems and processes.

• What You'll Do
  • Own ambiguous, cross-org AI bets end-to-end-identify the highest-leverage problems across the company, decide what to build, and drive it from prototype to durable production tool
  • Build and ship a high volume of internal apps, prototypes, and automations-going from a vague problem to a working tool in days, then iterating with users toward production quality
  • Define the reusable patterns and shared infrastructure the org builds on-reference architectures, internal libraries, MCP servers, eval harnesses, and templates that let others move faster and safer
  • Embed directly with teams across CX, Trust & Safety, ops, GTM, and EPD to find high-leverage problems, then build the solution alongside them
  • Wire AI into real business context-building RAG and retrieval pipelines, MCP servers, and agentic workflows grounded in Whatnot's data, with appropriate PII and access controls
  • Integrate AI tools with internal systems and data sources via APIs, connectors, and event-driven workflows so automations act on real state, not toy inputs
  • Scale the leverage-package successful builds into reusable skills and playbooks, and level up the whole company through enablement sessions, boot camps, and mentorship of other builders
  • Stay ahead of the AI landscape, evaluating and bringing in new models, tools, and patterns as the ecosystem evolves, and making the build-vs-buy calls
Who You Are
  • A prolific builder with senior judgment-you ship fast and iterate with real users, and you know where not to invest; you measure yourself by problems solved, tools adopted, and leverage created
  • Deep applied-AI fluency-extensive hands-on experience building with the current generation of LLM products (Anthropic, OpenAI, Google) and the production patterns around them: prompt engineering, RAG, MCP, agents, and evals
  • Systems-integration chops-you've connected AI to real data and tools through APIs, webhooks, and connectors, and you reason rigorously about reliability, latency, cost, and access controls
  • A pattern-setter and force multiplier-you've defined how teams build, mentored other engineers, and raised the technical bar for an org, not just your own output
  • A strong communicator-you can sit with non-technical users, translate their problems into software, and teach them to build for themselves
  • Low ego, high agency-you see inefficiency, build the fix, and bring people along with you
Benefits
  • Flexible Time off Policy and Company-wide Holidays (including a spring and winter break)
  • Health Insurance options including Medical, Dental, Vision
  • Work From Home Support
    • Home office setup allowance
    • Monthly allowance for cell phone and internet
  • Care benefits
    • Monthly allowance for wellness
    • Annual allowance towards Childcare
    • Lifetime benefit for family planning, such as adoption or fertility expenses
  • Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally
  • Monthly allowance to dogfood the app
    • All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!).
  • Parental Leave
    • 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence.

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