Senior Gen AI Software Engineer

Liftoff•United States (Remote), CA

15h•$211,000 - $270,000•Remote

About The Position

Liftoff is a leading AI-powered performance marketing platform for the mobile app economy. Our end-to-end technology stack helps app marketers acquire and retain high-value users, while enabling publishers to maximize revenue across programmatic and direct demand. Liftoff’s solutions, including Accelerate, Direct, Monetize, Intelligence, and Vungle Exchange, support over 6,600 mobile businesses across 74 countries in sectors such as gaming, social, finance, ecommerce, and entertainment. Founded in 2012 and headquartered in Redwood City, CA, Liftoff has a diverse, global presence. Join Liftoff as a Senior Gen AI Software Engineer and help shape the future of ad tech. As a key member of our Gen AI team, you’ll design and build AI-powered products for our demand-side business, helping teams turn complex data into better decisions and meaningful customer growth. You’ll work across the stack, building intelligent systems and data pipelines in Python, alongside the TypeScript and React experiences that bring those capabilities to users. You’ll partner closely with product, engineering, and customer-facing teams to identify high-impact opportunities, move quickly from prototype to production, and continuously improve what you ship. This is a hands-on role for an engineer who enjoys working at the intersection of AI, product, and software engineering. You’ll help define how Liftoff applies modern AI to real business problems, balancing experimentation with the judgment and engineering discipline needed to build useful, reliable products. This role is ideal for an engineer who thrives in ambiguity, enjoys experimenting with new technology, and is motivated by turning promising AI capabilities into products that create real value. You’ll tackle complex problems, validate new approaches, and drive meaningful improvements across Liftoff.

Requirements

Minimum Bachelors Degree and 8 yrs of relevant experience.
You are a seasoned software engineer who has built and operated meaningful production products, ideally including zero-to-one work spanning backend services, data, and user interfaces.
You have 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.
You are highly proficient in Python and comfortable working in TypeScript and React, with strong fundamentals in API design, data modeling, SQL, and testing.
You understand how to build the broader system around a model, including its data, tools, instructions, permissions, feedback loops, and measures of quality.
You can define success criteria, investigate failures, and use testing, feedback, and production signals to improve AI experiences over time.
You exercise strong product and engineering judgment, choosing when a problem calls for traditional software, an LLM-powered approach, or a thoughtful combination of both.
You communicate complex technical ideas clearly and collaborate effectively with domain experts and non-technical partners.
You are comfortable working through ambiguity, making informed decisions with incomplete information, and changing direction when evidence shows a better path.
You are a lifelong learner with strong but flexible opinions, and you thrive on giving and receiving constructive feedback.

Nice To Haves

Experience as an early engineer, startup founder, or in a similarly high-ownership environment where you moved quickly from ambiguous problems to shipped products.
Experience with advertising technology, campaign optimization, performance marketing, analytics products, or other data-rich B2B software.

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.
Evaluate new models and techniques pragmatically, adopting them when they materially improve product quality, capability, speed, or cost.
Mentor other engineers and help establish shared practices for designing, testing, and operating AI-powered products.