Senior Gen AI Software Engineer
New
L
LiftoffAd 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
Salary211,000 - 248,000 USD per year
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Job Details
- Experience
- 8 yrs of relevant experience.
- Required Skills
- PythonSQLTypeScriptReactData modelingGenerative AI
Requirements
- Hold a bachelor’s degree.
- Have 8 years of relevant experience.
- Have production software engineering experience, ideally spanning backend services, data, and user interfaces.
- Have shipped LLM-powered or AI-assisted products beyond a demo.
- Be highly proficient in Python and comfortable working in TypeScript and React.
- Have strong fundamentals in API design, data modeling, SQL, and testing.
- Understand how to build systems around models, including data, tools, instructions, permissions, feedback loops, and quality measures.
- Be able to define success criteria, investigate failures, and use testing, feedback, and production signals to improve AI experiences.
- Apply product and engineering judgment to choose between traditional software, LLM-powered approaches, or a combination.
- Communicate technical ideas clearly and collaborate with domain experts and non-technical partners.
Responsibilities
- Own generative AI product capabilities from workflow discovery and prototyping through implementation, rollout, measurement, and improvement.
- Prototype and validate AI solutions, then turn successful approaches into production-ready capabilities.
- Build agentic workflows that reason over campaign, customer, creative, and performance data, use tools, and produce structured results.
- Design how AI systems access and use relevant data, tools, and instructions to produce grounded results.
- Build production systems for AI workflows, including tool use, state management, failure recovery, and human review.
- Define testable interfaces between models and software to handle uncertain model behavior safely.
- Develop evaluation systems and instrumentation to measure task success, quality, adoption, business impact, latency, cost, and failure modes.
- Build Python services and TypeScript and React interfaces for customer-facing teams.
- Evaluate new models and techniques and adopt them when they materially improve product quality, capability, speed, or cost.
- Mentor engineers and help establish practices for designing, testing, and operating AI-powered products.
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