Senior Gen AI Software Engineer
New
L
Liftoff MobileAd Tech
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 ZoneFull-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
- Required Skills
- PythonSQLTypeScriptReactData modeling
Requirements
- Minimum Bachelors Degree and 8 yrs of relevant experience.
- Seasoned software engineer who has built and operated meaningful production products, ideally including zero-to-one work spanning backend services, data, and user interfaces.
- Shipped LLM-powered or AI-assisted products beyond a demo and understand the practical challenges of reliability, context, tool use, provider changes, latency, cost, and changing model behavior.
- Highly proficient in Python and comfortable working in TypeScript and React.
- Strong fundamentals in API design, data modeling, SQL, and testing.
- Understand how to build the broader system around a model, including its data, tools, instructions, permissions, feedback loops, and measures of quality.
- Can define success criteria, investigate failures, and use testing, feedback, and production signals to improve AI experiences over time.
- Exercise strong product and engineering judgment, choosing when a problem calls for traditional software, an LLM-powered approach, or a thoughtful combination of both.
- Communicate complex technical ideas clearly and collaborate effectively with domain experts and non-technical partners.
- Comfortable working through ambiguity, making informed decisions with incomplete information, and changing direction when evidence shows a better path.
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.
- Design how AI systems access and use relevant information, including the data, tools, and instructions needed to produce useful grounded results.
- Build the systems that make AI workflows reliable in production, including tool use, state management, failure recovery, and appropriate boundaries for human review.
- Define clear, testable interfaces between models and software so uncertain model behavior can be handled safely within dependable product systems.
- 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 instrumentation needed to understand quality, adoption, business impact, latency, cost, and failure modes in production.
- Apply appropriate safeguards for customer data, system access, and high-impact workflows.
- Build the Python services and TypeScript and React interfaces that turn these capabilities into cohesive products for customer facing teams.
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