Senior Gen AI Software Engineer

New

United States (Remote). This role is eligible for full-time remote work in one of our entities: CA, CO, ID, IL, FL, GA, MA, MI, MN, MO, NJ, NV, NY, OR, PA, TX, UT, and WA., Pacific Standard Time Zone preferredFull-TimeSenior

SalarySF Bay Area, Los Angeles/Orange County, NYC, Seattle: $230,000 - $270,000. All other cities and towns in our approved states: $211,000 - $248,000.

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Job Details

Experience: 8 yrs of relevant experience
Required Skills: PythonSQLTypeScriptReactData modelingGenerative AI

Requirements

Minimum Bachelors Degree and 8 yrs of relevant experience.
Seasoned software engineer with experience building and operating production products, including zero-to-one work.
Shipped LLM-powered or AI-assisted products beyond a demo.
Highly proficient in Python.
Comfortable working in TypeScript and React.
Strong fundamentals in API design, data modeling, SQL, and testing.
Understanding of the broader system around a model, including data, tools, instructions, permissions, and feedback loops.
Experience investigating failures and using production signals to improve AI experiences.
Strong product and engineering judgment.
Clear communication of complex technical ideas.

Responsibilities

Own generative AI product capabilities end to end, from understanding user workflows and prototyping an approach through implementation, rollout, measurement, and ongoing improvement.
Rapidly prototype and validate AI solutions, using focused experiments to test user value and technical feasibility, then turn what works into production-ready capabilities.
Build agentic workflows that can reason over campaign, customer, creative, and performance data, use well-defined tools, produce structured results, and hand control back to a person when appropriate.
Partner closely with decision makers and subject matter experts to understand their workflows, constraints, and business context, then integrate AI agents into daily work in practical and useful ways.
Build the systems that make AI workflows reliable in production, including tool use, state management, failure recovery, and appropriate boundaries for human review.
Develop evaluation systems that measure whether AI features accomplish the intended task, using realistic examples and an appropriate combination of automated checks and human judgment.
Build the Python services and TypeScript and React interfaces that turn these capabilities into cohesive products for customer facing teams.

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