Senior Gen AI Software Engineer

About the Role

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.

What You'll Do

• 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 technologies.